Third Parties and Police Use of Lethal Force: Evidence from the Mapping Police Violence Database
Lethal force, Third Parties, Police Citizen Interactions, Use of Force
Over recent years media coverage has highlighted the use of excessive force by some police officers. The use of lethal force towards black and other ethnic minority citizens has been identified as a cause for significant concern. Research in the bystander literature and in non-fatal force policing contexts has identified that third parties can have positive impacts in reducing the severity of these incidences. The role of third parties in fatal force events, however, has not been investigated. This is something which the current study seeks to address. The Mapping Police Violence database was used to identify a year’s worth of lethal force events in the US. Newspaper articles relating to these incidents have been coded in line with a predefined coding framework to examine the presence of third parties in these incidents, and the nature of any social relationships with third parties in relation to the type of lethal force utilised. The results revealed that third parties were present in just under half of incidences and that the presence of a third-party with a pre-existing social relationship to the citizen was associated with a lower likelihood of officers utilising forms of ‘less lethal’ force to the extent that it results in a citizen fatality. These findings highlight the potential importance of third parties in understanding the nature of lethal police citizen interactions, and also the potential protective role the presence of known others may have in reducing the likelihood of officers excessively utilising forms of less lethal force.
A secondary data analysis was utilised to examine the presence of third parties in incidences of police use of lethal force. The Mapping Police Violence database (Mapping Police Violence, 2020) was the primary dataset utilised for the study. This is a freely available and open public database compiled by researchers in the US which aims to provide a record of all police involved deaths in the US. This database has been recording police involved deaths in the US since 2013, primarily gathering information through news articles published by various American news outlets. The type of force engaged in by officers that resulted in death was utilised as the outcome variable. The predictor variables were the presence of third parties, the presence of any known third parties, or unknown third parties, the number of officers present, the presence of other emergency services, the location of the incident, the race of the citizen, the gender of the citizen, the alleged presence of a weapon, the initial reason for the encounter, the presence of any digital technology capturing the event and the level of threat posed to the officer. The Mapping Police Violence database records multiple variables in relation to these incidences, including individual and situational factors. Several of the predictor variables included in the current study have been gathered from this dataset; specifically, the type of lethal force used, the alleged presence of a weapon, the race of the citizen, the gender of the citizen, the level of threat posed to the officer, the initial encounter reason and the presence of a body worn camera. Within the current study, most of these variables have been used as recorded in the dataset, however, the level of threat posed to the officer has been recategorized. The multiple different levels of threat recorded in the dataset have been regrouped into three categories: attack (indicating the greatest level of threat to the officer), other (referring to any other level of threat), and none (for incidences in which it was clear there was no threat to the officer). In the original data only the presence of a body worn camera is recorded. For the current study this variable has been transformed to include the presence of any digital technology capturing the event, such as CCTV or smartphones, as research has found that the presence of any digital technology and not only a body camera can affect police citizen interactions (Shane et al., 2017). The Mapping Police Violence database records the citizen’s cause of death in relation to the type of force utilised. In incidences where multiple types of force have been identified as contributing to the citizen’s death, the database records a list of all types of force involved. The types of force included in the database include gun, taser, pepper spray, baton and physical restraint. For the current study, these types of force have been grouped, to provide an outcome variable with fewer levels. The grouping of the outcome variable has been done in line with previous research looking at police use of force, which identified a gun as a distinct type of force due to the increased risk of lethal outcomes. The other types of force are grouped into a second category of other types of ‘less lethal’ force, as these types of force have been identified as alternatives to the use of a gun, which would be expected to reduce the likelihood of a citizen fatality (Sheppard & Welsh, 2022). In incidences where multiple types of force were used, the most severe form of force has been recorded; for example, if the cause of death is attributed to a gun and a taser, then this incident would be recorded as a gun as the type of lethal force utilised. The dataset contains links to the news articles which have been used to gather information regarding each of the individual police involved death incidences. The variables included in the current study relating to the presence of others were gathered by coding these news articles which are linked in the database to the individual incidences of police involved deaths between 6th March 2022 – 6th March 2023, providing a sample of 1,257 police involved deaths. News articles are a source of information which have been identified as having certain limitations, particularly relating to potential media bias in the reporting of crime related stories (Lawrence, 2000). Research looking at the reporting of police use of force incidences by newspapers, however, has found that for many factors there was consistency between news reports and police reports of the same incidents (Ready et al., 2008). For the current study, news articles are utilised due to the promise they provide in allowing the events of police involved deaths to be examined in relation to the presence of third parties. To identify the relevant incidences for the current study, three primary exclusion criteria were applied prior to the coding of the news articles. Firstly, to identify incidences with news articles with sufficient information to allow the presence of third parties to be examined, a minimum word count of 150 words was required in at least one of the associated news articles. Secondly, as the study’s primary interest was in the use of lethal force, which involves an on-duty officer using force, only incidences relating to on duty officers were included. Finally, incidences in which the use of force by the officer was accidental, such as car crashes that police officers were involved in, were excluded, as these events have different characteristics to those in which officers intentionally engage in the use of force towards a citizen. The application of these exclusion criteria left a sample of 1052 incidences of police use of lethal force. To investigate the presence of others in these incidences, prior to the analysis a predefined behavioural coding scheme (Philpot et al., 2019) was created and applied to the news articles to capture the presence of third parties. This coding scheme contained 12 individual items capturing the presence of third parties and any social ties between third parties and the citizen involved in the incident (See Appendix A for the full coding scheme). Two additional items were included to capture the presence of multiple officers or other emergency services. One code regarding the location of the incident was also included to capture whether it occurred in a public, semi-public or private location. Each of the items were coded for presence with a 1, their absence recorded with a 0, or if it was not clear whether this item was present a 99 was recorded. In total 15 codes were included in this behavioural coding scheme. Here are some examples of these codes relating to the presence of third parties: “The presence of a third-party with a pre-existing social connection to the primary citizen involved” “The presence of more than one officer” “The presence of a third-party with no pre-existing social connection to the primary citizen involved” To facilitate the process of coding the news articles in line with the coding scheme, a Qualtrics survey (https://www.qualtrics.com) was created. This survey presented the individual items within the coding framework in a questionnaire format, allowing the items to be coded in the format of closed ended responses to questions relating to the presence of third parties. The responses from the survey were then transferred to an Excel document to allow the data to be prepared for analysis. Ethical approval has been obtained for this study. The study has been reviewed and approved by a member of the Lancaster University Psychology Department, the ethics partner of the supervisors. The reliability of the coding scheme and its application to the news articles was assessed through the double coding of 10% of the sample by a second researcher separately to the primary researcher. To assess the level of agreement between the two researchers for each variable, Gwet’s AC1 (Gwets, 2014) coefficient was calculated. In line with the recommendations of Landis and Koch (1977), the resulting coefficients were interpreted in the following way: a value of 0.4 or above indicating moderate agreement, a value of 0.6 or above indicating substantial agreement, and finally a value of 0.8 or above, indicating almost perfect agreement between raters’ scores. For 13 of the variables an agreement level of substantial or almost perfect was reached, as seen in table 1 (appendix B). For the variable relating to the third-party being a friend of the citizen there was no variation in responses (i.e., 100% agreement), and therefore a coefficient could not be calculated. For the location variable, only a moderate level of agreement was found, as a result this variable was excluded for the purpose of analysis. Figure 1 depicts a flowchart of the process undertaken to sample the relevant incidences. The first part of the flowchart shows the initial process that was undertaken to identify all police involved deaths recorded in the Mapping Police Violence database in the prior 12 months. Following the initial data collection procedure descriptive statistics were run which highlighted that in the initial sample of 1052 incidences there was very limited variation in the outcome variable of the type of lethal force utilised by officers, with 990 incidences involving a gun as the primary cause of death, and only 62 incidences involving other forms of force. In this initial sample a citizen’s cause of death not involving a gun would statistically be considered a rare event, which would have presented challenges in utilising this variable as the outcome in any subsequent analyses. In line with the recommendations of research (Shaer et al., 2019), an oversampling approach was chosen to overcome the limitations of having a rare event in the outcome variable, with further incidences in the dataset that did not involve a gun as the cause of death being oversampled so at least 10% of the sample involved a cause of death other than a gun. As can be seen in figure 1, for these incidences to be as similar to the primary sample as possible, they were only sampled for the three preceding years to limit any additional sample variation that may have been introduced by sampling a wider date range. This led to the identification of a further 182 incidences where the citizen’s cause of death did not involve a gun. The same exclusion criteria were then applied to this sample, with a further 65 incidences excluded, leaving a sample of 117 additional incidences which were coded in line with the same procedure as the initial sample. This oversampling procedure led to a final sample of 1169 incidences. The data analysis involved chi square tests of independence, to examine whether the presence of others during fatal police citizen interactions had a statistically significant relationship with the outcome variable of the type of lethal force utilised by officers. Due to the exploratory nature of the study there was not a predicted direction or nature of the relationship between the predictor variables relating to third-party presence and the type of fatal force utilised by officers (McIntosh, 2017). Prior to the main analyses, descriptive statistics were run to investigate distributions within variables and to allow any rare event variables to be identified.
Grasping Ability in Virtual Reality: Effects of Eating Disorders on Perceptions of Action Capabilities
Action Capability, Eating Disorder, Interoceptive Awareness
Knowledge of one’s body size is vital to be able to accurately judge an object’s size. For example, knowing the length of your arm is crucial to estimating the maximum distance reachable. Accurate perception of action capabilities is the result of a healthy mental body representation at a conscious and implicit level. This ability to use one’s mental body representation in action perception is assumed to be distorted in individuals with eating disorders (ED). However, unlike prior research, this study will be investigating both the effect of body image and schema distortion on action capabilities. Thus, this study will assess whether the ability to update one’s perception of their action capabilities in response to morphological changes is altered in individuals with EDs. The experiment had participants (N = 20) embody small (50% of hand size), normal, and large (150% of hand size) avatar hands (in virtual reality) and then estimate the maximum size of a box graspable. The size of the box, beginning as either large or small across all three conditions, was manipulated to observe haptic perception in participants. We found that individuals with ED showed similar estimates despite embodying different hand sizes alluding to their inability to successfully update their haptic perceptions. Low interoceptive awareness and body image disturbances were the root cause of this perceptional flaw in eating-disordered individuals. Treatment focused on improving the altered IA and implicit distortions in body schema could improve haptic perception in ED individuals.
A priori power analysis was conducted through the G*Power software (Faul et al., 2007) to determine the sample size required to achieve adequate power (N = 30). The required power (1- β) was set at .80 and the significance level (α) was set to .05. Based on Readman et al. (2021), who used the same methodology as this study, we anticipated a large effect size of 0.9. This was deduced as this study obtained a ηp2 of .49 with a sample of N =30. For the frequentist parameters defined, a sample size of N = 3 is required to achieve a power of .80 at an alpha of .05. EDs are also notoriously variable. Given that previous studies using similar methodologies have typically recruited between 20-30 participants (Readman et al., 2020; Lin et al., 2020), we elected to recruit 30 participants (15 per condition). However, this study was only able to recruit 23 participants in total. 22 participants from Lancaster and Lancaster University (seven males, 15 females) aged between 18-30 (Mage = 21.73, SDage = 1.98) participated in this study. Two participants were removed due to being extreme outliers resulting in the present dataset (N = 20; Mage = 21.65, SDage = 2.06). Amongst participants of this study, seven participants disclosed a diagnosis of ED. In accordance with the revised Edinburgh Handedness Inventory (R-EHI) classification system (Milenkovic & Dragovic, 2013), the majority of the participants (N = 19) were right-handed, with only one participant being left-handed. Borderline to high levels of anxiety, as measured through the Hospital Anxiety and Depression Scale (HADS; Stern, 2014), was observed in 16 participants, while seven participants showed similar levels of depression. Eating Disorder Inventory (EDI): Participants with ED were also asked to complete the EDI. It is a self-report questionnaire that can assess the presence and level (depending on the estimate) of AN, BN, and Binge Eating Disorder (BED) (Augestad and Flanders, 2002). It consists of 64 items, with eight subscales measuring dimensions such as drive of thinness, body dissatisfaction, perfectionism, interpersonal distrust, and IA (Garner, Olmstead, & Polivy, 1983; Vinai et al., 2016; Santangelo et al., 2022). Seven participants had ED while the remaining formed the healthy control group.​ Design This study includes variables in a 2 (Between factor: Group – Control vs. ED) x 3 (Within: Hand size – small vs. normal vs. large) factorial design. The dependent variable (DV) is the grasping ability, and the independent values are the groups involved and the hand size conditions. All participants of each group experienced all conditions of the hand size. The order of condition completion was randomised across participants through use of a Latin square method. Such counterbalancing allows for the control of confounding/extraneous variables and diminishes order and sequence effects, improving internal validity (Corriero, 2017). Stimuli and Apparatus Participants were seated an arm’s length away from the front of a standardized table. Unity 3D© Gaming Engine with the Leap motion Plugin was used to create a virtual environment in 3D VR colour. Participants were able to view this environment through an Oculus Rift CV1 Head Mounted Display (HMD). The HMD displayed the stereoscopic environment at 2,160 × 1,200 at 90 Hz split (Binstock, 2015). Head and hand movements were tracked in real-time by the HMD and the Leap motion hand-tracking sensor attached to the HMD. The HMD ensured that the participants’ perspective was updated in real-time. Hand movements were updated in accordance with the virtual hand that was mapped onto the participant’s natural hands. Leap Motion for Unity provided assets such as avatar hands based on actual human hands. The virtual environment was visible to the participants in a first-person perspective adjusted to their height. The VR display is comprised of a model room, with a table located in the middle. Upon this table were either two white dots (Calibration trials) or a white box (Test trails). Questionnaires Revised Edinburgh Handedness Inventory (R-EHI). Participants’ handedness was deduced using the R-EHI. The modified version of the inventory was used as it accounted for and improved the inconsistencies and validity compared to the past questionnaire (Milenkovic & Dragovic, 2013). Participants are estimated on handedness depending on their preferences of either hand for doing activities such as writing, drawing, throwing a ball, etc. Hospital Anxiety and Depression Scale (HADS). The HADS questionnaire was also provided to all participants to assess the presence of borderline or abnormal levels of anxiety and depression in them. It is a quick questionnaire consisting of seven questions each for anxiety and depression, with both being scored separately (Stern, 2014). Procedure Participation in this study took up to an hour of the participant’s time. It was conducted in the Whewell Building of Lancaster University. Participants were recruited partly through opportunity sampling, and advertisements. All participants received £5 for their contribution to this study. All participants were native English speakers, had normal or corrected vision, and had no motor difficulties. Participants provided informed consent through a consent form signed before the onset of the study. They were also provided a debrief sheet and were verbally debriefed at the end of the experiment. The methodology of this study mirrors that of Readman et al. (2021). The experiment was conducted in a virtual environment (VE) through a VR device. The inclusion of VR allows for controlled changes to grasping ability, with responses collected similar to how an individual would act in the real world (Normand et al., 2011). Moreover, the inclusion of VR enabled interactions with the morphologically altered virtual body in real-time, and in a similar physical environment through the immersive system built through the head-mounted displays (HMD) and motion sensors (Gan et al., 2021). Participants completed the R-EHI, EDI, and HADS questionnaires before beginning the experiment. Participants were asked to don the HMD and introduced to the virtual environment through a brief demonstration. They were given approximately 5 minutes to explore the environment, to familiarise themselves with the immersive VR experience and ensure no undue effects occur. Participants completed three experimental conditions: Normal hand size, constricted hand size (50% of their hand size), and extended hand size (150% of their hand size). Each condition consisted of calibration and test trials. Calibration trials. Participants were presented with the virtual table upon which two horizontally spaced dots were located. Using their dominant hand, participants were asked to touch the left-most dot with their left-most digit and then touch the right-most dot with the right-most digit of their dominant hand. This occurred for 30 trials to ensure that the participant has habituated to the virtual hand. Test trials. The participants were instructed to place their hands behind their backs, out of sight. The Leap Motion sensor was then temporarily paused to ensure that the virtual hands are not visible to the participants. On ensuring this position, participants were then presented with a block in the VE, that they had to envision they could grasp with their dominant hand from above. The size of the block was manipulated, making it either larger or smaller, with each alteration causing 1cm changes. The participant was asked to tell the researcher when the block reflects the maximum size that they would be able to grasp. The final size was saved before the participant was presented with another block. Grasping was defined to participants as the ability to place their thumb on one edge of the block and extend their hand over the surface of the block and place one of their fingers on the parallel edge of the block. This grasp was also demonstrated to participants. Participants completed four test trials; in two test trials, the block started small (0.03 cm) and was made larger. In the remaining two trials the block started large (0.20 cm) and was made smaller. This was done to omit the hysteresis effect, which would cause prior visual stimuli to influence later perception (Poltoratski & Tong, 2014). Therefore, four grasp-ability estimates were obtained for each experimental condition. This study received ethical approval from Lancaster University Psychology department. Data Analysis An Analysis of Variance (ANOVA) is a statistical model used to examine differences in means (Rucci & Tweney, 1980). The present dataset contains both between-subjects (group) and within-subjects (hand size) factors. Thus, a mixed ANOVA would allow us to compare these variables and the means of the groups they are cross classified with. This is a two-way analysis as there are two independent variables (group and hand size) but only one DV (grasping ability estimate). Analysis through ANOVA is appropriate for this dataset as the effect of both variables in this study can be studied on the response estimate (Field, 2009). This study aims to establish the effect of group and hand size on grasping ability (GA). Therefore, a mixed ANOVA would help us identify the significant effect of either factor on the GA estimate and examine their interaction effect. Results of the mixed ANOVA analysis would help assess whether individuals with ED do update to changes in morphology. Data Preparation The present dataset combined demographic, physicality, and questionnaires related (EDI, R-EHI, HADS) information and GA estimates across the hand size conditions (small vs normal vs large). GA estimate of each condition was further sub-categorized into whether the box started large or small with four trials each. Averages of these four trials for the small starting box and large starting box for each condition was taken forming the mean grasp-ability estimates (cm).
An investigation into the effect of climatic, ambient temperature on societal-level income inequality
Previous research has revealed contradictory findings concerning the relationship between temperature and behaviour. Some studies have found a warmer-is-better effect; warmer temperatures are associated with enhanced interpersonal interactions, including pro-social behaviours. Whereas other studies have found a warmer-is-worse effect; warmer temperatures are associated with negative social behaviours such as conflict, societal instability, crime and aggressive behaviours. The present study investigated the relationship between climatic, ambient temperature and societal income inequality. Climatic temperatures and Gini ratios (a measure of income inequality) were sourced from online databases for 29 countries across a range of time periods that fell between 1961 and 2015. A panel linear model analysis revealed that climatic temperature had no direct effect, nor lagged effect on income inequality. Therefore, the findings are not congruent with the warmer-is-better literature or the warmer-is-worse literature. Despite the null effect, the present study provides a further data point towards the debate concerning the effect of temperature on behaviour.
Firstly, the study required Gini ratios of disposable, equivilsed income. The Gini ratio is a measure of income inequality whereby a ratio of 1 reflects perfect inequality (i.e. one household receives all of the income) and a ratio of 0 is indicative of perfect equality (i.e. income is equally shared across households). The ratio was calculated from disposable income, which is income after the deduction of taxes and social security charges. Additionally the ratio was equivilised which means that the ratio was adjusted to account for different sizes and compositions of households. Secondly, the study required mean climatic temperatures in degrees celsius. Procedure Gini ratios for 29 countries belonging to the organisation for economic co-operation and development (OECD) were sourced from several online databases that had calculated the ratios. The countries and years used in the present analysis were somewhat dictated by the availability of Gini ratios online and as a result the OECD countries Australia, Chile, Israel, Japan, Korea and Mexico could not be included in the present analysis and the year ranges included fell between 1961-2015. See table 1 for the sources of Gini ratios, and the countries and years for which Gini ratios were available. It is important to note that the surveys from which the Gini ratios were calculated were slightly different, for example, some had different definitions of a ‘household’. Additionally, not all of the sources provided the exact Gini ratio calculation used. Table 1: Online sources from which Gini ratios were obtained from several countries across several, differing, time periods Country Time period Source of Gini ratios Austria (AUT) 1995-2001, 2003-2015 Eurostat, European Union Statistics on Income and Living Conditions (2017). Belgium (BEL) 1995-2001, 2003-2015 See Austria. Canada (CAN) 1976-2015 Statistics Canada (2017). Czechoslovakia (CZE) 2001, 2005-2015 See Austria. Denmark (DEN) 1987-2015 Statistics Denmark (2017). Estonia (EST) 2000-2002, 2004-2015 See Austria. Finland (FIN) 1987-2014 OECD Data (2017) France (FRA) 1995-2002, 2004-2015 See Austria. Germany (GER) 1984-2013 German Socio-economic Panel Study (2015) Greece (GRE) 1995-2001, 2003-2015 See Austria. Hungary (HUN) 2000-2002, 2005-2015 See Austria. Iceland (ISL) 2004-2015 See Austria. Ireland (IRL) 1995-2001, 2003-2015 See Austria. Italy (ITA) 1995-2001, 2004-2015 See Austria. Latvia (LVA) 2000, 2005-2015 See Austria. Luxembourg (LUX) 1995-2001, 2003-2015 See Austria. Netherlands (NED) 2000-2014 Netherlands Central Bureau of Statistics (2017) New Zealand (NZL) 1984, 1988, 1990, 1992, 1994, 1996, 1998, 2001, 2004, 2007, 2009-2014 Perry (2016) Norway (NOR) 1986-2015 Statistics Norway (2017). Poland (POL) 2001, 2005-2015 See Austria. Portugal (POR) 1995-2001, 2004-2015 See Austria. Slovakia (SVK) 2005-2015 See Austria. Slovenia (SVN) 2000-2002, 2005-2015 See Austria. Spain (ESP) 1995-2002, 2004-2015 See Austria. Sweden (SWE) 1975, 1978-2013 Statistics Sweden (2017). Switzerland (SWI) 2007-2015 See Austria. Turkey (TUR) 2002, 2006-2013 See Austria. United Kingdom (UK) 1961-2014 Institute for fiscal studies (2016) United States (USA) 1967-2013 Proctor, Semega & Kollar, M. A. (2016). Temperatures were sourced from the Climate Change and Knowledge Portal (2017) which contained the mean temperatures in degrees celsius for every country that was included in the present analysis for each month from years 1901-2015. Because we obtained mean Gini ratios for each year, we calculated mean climatic temperatures by calculating the average of the 12 months for each year, and country, that a Gini ratio was obtained. All Gini ratios and temperatures were accessed on 28th June 2017. Design and analysis In the present study the predictor variable was temperature and the outcome variable was Gini ratios. Data was collected for 29 countries across differing time periods ranging from 8-53 years resulting in a dataset with 594 observations. The dataset was a panel dataset whereby the data was cross-sectional (i.e. across countries) and longitudinal (i.e. across time periods) and unbalanced because of the differing time periods for each country. Therefore, to analyse the effect of temperature on Gini ratios, the plm package (Croissant & Millo, 2008) in R (R development core team, 2012) was used because this analysis has been designed to account for panel, unbalanced datasets. Additionally this package could determine whether country and time had an effect on Gini ratios and how these effects should be accounted for. The general linear model for the data set was (Croissant & Millo, 2008): yit = α + Txit + µi + t + it i = country t = time yit = Gini ratios α = intercept Txit the coefficient of the effect of temperature on Gini ratios µi = the unobserved error as a result of the effect of country on Gini ratios t = the unobserved error as a result of the effect of time on Gini ratios it = residual/idiosyncratic error, independent of the predictor and individual error components The specific model that was used in the present analysis was dependent on the existence of country effects (i.e. µi) and time effects (i.e.t) and the nature of these effects. There are three potential ways to model the panel datasets when estimating the effect of temperature on Gini ratios (Croissant & Millo, 2008): 1 – Pooled model; where time and country have no effect on Gini ratios (i.e. µi =0, t =0). Thus, the pooled models estimation is consistent and efficient, and applies across countries and time. 2 – Fixed effects model; where there are effects of country and/or time on Gini ratios and these effect(s) are correlated with the predictor variable, temperature. These correlated effect(s) result in the pooled models’ estimation being inconsistent because the estimates differ across countries and/or across time. Therefore, the fixed effects model accounts for the heterogeneity between countries and/or time by treating country and/or time as parameters to be estimated in the model and consequently the model gives consistent estimates of the effect of temperature on Gini ratios. This model can be one-way (i.e. the effect of country or time are taken into account) or two-way (i.e. the effects of country and time are taken into account). 3 – Random effects model; where there are effects of country and/or time on Gini ratios and these effect(s) are uncorrelated with the predictor variable, temperature. As a consequence of these uncorrelated effects, although the pooled models estimation is consistent, this estimation is inefficient. Thus, the random effects model accounts for the heterogeneity between countries and/or time by treating country and/or time as a separate error component(s) in the model and consequently the model gives consistent and efficient estimates of the effect of temperature on Gini ratios. Similar to the fixed effects model, the random effects model can be one-way or two-way. To determine which model was appropriate for the dataset, and thus to determine the nature of the effects of country and time, we performed exploratory (i.e. graphical representations) and confirmatory (i.e. hypothesis testing) analyses. Firstly, we used graphs to visualise whether the intercepts were heterogeneous across countries and time as heterogeneity would suggest that the pooled model (i.e. model 1) was not appropriate. Following this, to determine whether the pooled model was appropriate for the dataset, we used the F test of stability, which by default tests whether the same coefficients applied to each country. Following this F test there were two potential routes. (i) If the analysis revealed that the same coefficients applied across countries, we would then implement an F test of stability to test whether the same coefficients applied across time. If the second F test revealed that the same coefficients applied across time, a pooled model (i.e. model 1) would be used as this would provide a consistent and efficient estimation. Whereas if the second F test revealed that the coefficients did not apply across time, this would suggest that the pooled model was not appropriate and thus a Hausman test would be required to determine whether time should be modelled as a fixed effect (i.e. one-way fixed effects model; model 2) or random effect (i.e. a one-way random effects model; model 3). (ii) If the analysis revealed that coefficients did not apply across countries this would suggest that a pooled model (i.e. model 1) was inappropriate for the dataset. Consequently a langrage multiplier test would be required to determine whether a one-way or two-way effects model should be used i.e. whether country alone had an effect on Gini ratios (i.e. one-way) or whether country and time had independent significant effects on Gini ratios (i.e. two-way). Secondly, a Hausman test would be necessary to determine whether the effect(s) should be modelled as fixed (i.e. fixed effects model; model 2) or random (i.e. random effects model; model 3). Once a model had been specified, we estimated the direct and lagged effect of temperature on Gini ratios. Finally, we carried out diagnostic testing to analyse whether there was serial correlation or cross-sectional independence in the idiosyncratic errors of the model that would need to be dealt with.
The effects of code switching in the level of persuasiveness of advertising and marketing messages on bilingual consumers.
Bilingualism Code-switching Language Manipulation Advertising Communication Language Comprehension/Cognition
Bilingualism and advertising are two concepts which are not commonly related, but based on recent statistics they definitely should be. Recent numbers show that more than 50% of the world’s population is bilingual (Grosjean, 2010). However, there has been minimal research concerning bilingual consumers and how bilinguals may differently encounter advertising messages, based on their ability to speak two languages. The research that has been done, is primarily based on code switching; the practice of switching between languages during speech. It is a very common practice between bilinguals, which they use to better communicate and better express themselves during a conversation in a specific social context. This study will attempt to analyse the effects of language manipulation upon bilingual individuals, by implementing the concept of advertising and more specifically bilingual advertising. participants will firstly encounter a manipulation of attitude towards language, before encountering a set of advertising slogans of certain products, in a code-switched format. They will then have to rate the products, based on the persuasiveness of the advertising slogans.
Firstly, a manipulation of attitude towards the language took place. Participants were presented with a random mock article, either in Greek or English. Participants were then presented with four audio recordings of advertising messages/slogans of four different products. Slogans were either all in Greek or English and they were presented in the same code-switching direction; from primary to Secondary or from Secondary to primary. A single word was chosen from each slogan and was code-switched to the opposite language appropriately. Participants were then asked to evaluate the featured products based on the advertising message they heard. Evaluations were obtained through a series of six questions, asking the participant to rate the featured product on a Likert type scale, varying from one to six. These included: “poor/high quality”, “level of appeal”, “odds of recommending the product to others”, “odds of buying the product”, “mediocre/exceptional” and “bad/good”.
The Effects of Schema-typical and Atypical Contexts on Memory for Brand Names of Products
Distinctiveness effects Schema Memory Product recall Product recognition Brand recall Brand recognition Product-brand binding
The memory for an advertisement can be affected by the way it is constructed. In general, the more distinctiveness, the better memory performance. Traditionally, it has been assumed that the whole memory episode will be better remembered if it is featured by any odd element(s) because it is more attention-demanding and creates stronger memory traces. However, recent evidence suggests that the distinctiveness effect might not spread to everything; it might only affect those distinctive elements without necessarily affecting their linkages with other elements. Accordingly, regarding the advertisements, the memory for each element can be diverse. We manipulated the distinctiveness effect by composing products with schema-typical contexts (undistinctive condition) and schema-atypical contexts (distinctive condition). Participants observed 20 advertisements; 10 were schema-typical and another 10 were schema-atypical. They then completed recall and recognition tests which allowed us to explore how far the distinctiveness effect could extend. We found that only product recall and recognition in the schema-atypical condition were robustly enhanced, other variables were not significantly affected. These findings went against the traditional view and conform with the recent research. We discussed that, in the schema-atypical condition, the products and their contexts made each other distinctive, hence, they were better remembered. In contrast, the brand names and product-brand bindings were schema-neutral, thus, they did not receive more attention and not better remembered. The results were further interpreted to form some practical implications that improve advertising effectiveness.
The stimuli were 40 newly constructed print advertisements (in digital format). Print advertisements were employed because they allow the better experimental control (Keller, 1987). A half of these advertisements belonged to toiletries category (i.e. shampoo. sunscreen, and toothpaste), whereas another half belonged to foods category (i.e. pizza, sandwiches, and fried chicken). For each category, there were 10 types of products. For each product, there were two versions of its advertisement; schema-typical and schema-atypical (but only one of which was viewed by each participant). The schema-typical advertisements referred to the ones in which the product was bound with an expected context (i.e. a toothpaste appearing a bathroom scene), while the schema-atypical advertisements referred to the ones in which the product was bound with an unexpected context (i.e. a toothpaste appearing in a bedroom scene). In terms of the stimuli construction, there were three key elements for all advertisements, the first of which was the product, the second was the background or the scene illustration which was considered as the context of that advertisement, and the last element was the brand name. The first two elements were to form advertising pictures, and all together with the third one were to form complete advertisements. The researchers purchased stock images from Shutterstock website (https://www.shutterstock.com). The images purchased (product shots, backgrounds, and decorative elements) were then retouched and composted into the print advertising pictures using Adobe Photoshop (Adobe Photoshop CC 2015). All the advertising pictures were controlled not to include any text so that the only copy presented in each advertisement was its brand name. In respect of brand names, we invented new brand names for all 20 products. Each brand name was controlled to be easily pronounceable. They were names of between one to three syllables i.e. Hans, Raven, and Moana. The brand names, texts in Candara 48-point type, were placed on top of every advertising picture. Figure 1 shows examples of stimuli. Table 1 shows the List of products, brand names, their schema-typical contexts, and their schema-atypical contexts. The illustrations of all 40 advertisements can be found in Appendix A. Figure 1. Examples of stimuli Table 1 List of products, brand names, their schema-typical contexts, and their schema-atypical contexts Product Brand name Schema-typical context Schema-atypical context Toiletries Category 1 Soap Flounder Bathroom Garden 2 Shower gel Naveen Bathroom In the bus 3 Deodorant Megara Bathroom Library 4 Perfume Attina Bedroom Street 5 Sunscreen Moana Beach Kitchen 6 Shaving cream Hans Bathroom Office 7 Toothpaste Pongo Bathroom Bedroom 8 Talcum powder Fauna Bathroom Beach 9 Shampoo Rolfe Salon Forest 10 Lipstick Armoire Office Cooking table Food Category 11 Sandwich Duchess Kitchen On the stairs 12 Fried chicken O’Malley Kitchen Yoga room 13 Yogurt Rialey Kitchen In the bus 14 Energy bar Gaston Sport field Bedroom 15 Pizza Linguini Restaurant Bathroom 16 Pasta Tony Kitchen On the bed 17 Soup Perdita Kitchen Gym 18 Raw burger Gus Kitchen Study room 19 Ice-cream Bo Bo Street Library 20 Fresh fruit Raven Garden Bathroom In addition, there was an effort to provide the variability of context for both schema-typical and schema-atypical advertisements. To illustrate, for the schema-typical advertisements, regarding the advertisements of toiletries category, from the total of 10 products, six of them were bound with a bathroom scene as their schema-typical context, while another four products were bound with other different schema-typical contexts (i.e. a beach scene for sunscreen). Similarly, for foods category, six products were bound with a kitchen scene as their schema-typical context, while another four products were bound with other different schema-typical contexts (i.e. a restaurant scene for pizza). Furthermore, for the schema-atypical advertisements, all 20 products had their own different schema-atypical contexts. For example, a forest scene was for shampoo, while a Yoga room was for fried chicken. Consequently, despite the effort to make the context of schema-typical advertisements more varied, there was probably more variability for the schema-atypical ones. Moreover, regarding the judgement of schema typical or atypical context, it was initially set up based on researchers’ perspective. Then, a pilot study was conducted on five participants where they were asked to judge whether the contexts were schema-typical or atypical for a particular product. All five participants judged each context to be typical and atypical as judged by the researchers, for all products listed. Furthermore, we constructed some additional materials to be used in the recognition test which were 20 foils of similar product images and 20 foils of similar brand names. As for the foil product images, we purchased another set of stock images (product shots and decorative elements) to be retouched and composted into another 20 product images as icons in isolation. Each foil was designed after one of the target product images, for example, we constructed the foil image of a toothpaste tube to be paired with the target image of a toothpaste tube. These two images were controlled to look similar in terms of product type and size, but different regarding the product design (packaging and colour scheme). As for the foil brand names, we further invented 20 similar brand names, 10 for toiletries category and another 10 for foods category. All foil brand names were controlled to have the same characteristics as the target brand names; names of between one to three syllables which were easily pronounceable. Design and data analysis strategy The overall design and the variables. A repeated measures design was employed in this study. The within-subjects independent variable was the advertising context which consisted of two levels; schema-typical and schema-atypical. There were six dependent variables examined in separate analyses. The first three variables were from the recall test including the percentage of correctly recalled products (product recall), the percentage of correctly recalled brand names (brand name recall), and the percentage of correctly recalled product-brand bindings (product-brand binding recall). The first two variables were simply calculated from the number of correct answers divided by the total number of advertisements of each level. These variables were to answer whether the performance of products and brand names recall would be better if the advertising contexts were different from their typical schemas. For the third variable, the product-brand bindings recall, it was calculated based on the number of correctly recalled sets (which were counted when the products were written together with their matching brand names) divided by the number of correctly recalled products. Hence, this third variable was to explore that when people recall the products, how much would they extend their memory to the brand names. Likewise, the other three dependent variables were from the recognition test including the percentage of correctly recognized products (product recognition), the percentage of correctly recognized brand names (brand name recognition), and the percentage of correctly recognized product-brand bindings (product-brand binding recognition). Similarly, the fourth and fifth variables were calculated by dividing the correct answers by the total number of advertisements of each level. These variables were to answer whether the performance of products and brand names recognition would be better if the advertising contexts were different from their typical schemas. Also, for the sixth variable, the product-brand bindings recognition, it was calculated based on the number of correctly recognized sets (which were counted when participants picked the right choices of product images and their matching brand names concurrently) divided by the number of correctly recognized products. Hence, this last variable was to explore that when people recognize the products, how much would they extend their memory to the brand names. Presentation phase. In terms of experimental design, firstly, 20 advertisements were presented to participants. For counterbalancing purpose, 32 participants were equally divided into four groups (eight participants in each). Each group was bound with a different set of advertisements. Each set consisted of 20 advertisements, 10 from toiletries category and another 10 from foods category. From 10 toiletries advertisements, half of them were the schema-typical advertisements and another half were schema-atypical. From five schema-typical advertisements, three of them had a bathroom as their context, and another two had other typical contexts. The arrangement mentioned above was also applied to the foods category advertisements; three schema-typical advertisements were bound with a kitchen scene, another two schema-typical advertisements were bound with other schema-typical contexts, and five different schema-atypical advertisements. Appendix B shows four different sets of stimulus. However, the actual orders of advertisements presented to participants were not the same as shown in the Appendix B, as all 20 advertisements in each set were then randomly mixed. Hence, the positions of advertisements were different in each set to minimize the order effect. Additionally, all the advertisements were presented on a laptop screen (13-inch MacBook Air) and each of them was shown for 10 seconds, using a timed PowerPoint display. After the presentation of stimuli, there was a distractor task for two minutes. Immediately after the two-minute interval, participants were administered a free recall test followed by a recognition test. In addition, to achieve the most appropriate study design, prior to the establishment of the final experiment procedure, we ran a small pilot study to determine a suitable memory interval (the duration of the distractor task). We had two participants (two females, mean age = 25 years) do the pilot study which 10-minute interval was employed, and we found that it led to a ceiling effect for product recognition but a floor effect for brand name recall and recognition. Therefore, we decided to cut down this interval to only two minutes. Test phase. For the free recall test, participants were asked to write down every product and brand name which they could remember in the answer sheet. Figure 2 shows the presented slide for the recall test. For the recognition test, we separated it into two subsections; the toiletries subsection and the foods subsection. In each subsection, there were 10 questions referring to all 10 products in that category. Thus, there were the total of 20 main questions in this recognition test. The questions were also presented on the same laptop screen (13-inch MacBook Air). The toiletries-category questions were presented first, followed by the foods-category questions. Figure 2. The PowerPoint slide used in the recall test In respect of recognition test construction, for each question, there were two sub-questions; product question and brand name question. For each product question, there were two choices (A and B) which included the target image of product and the foil of similar product. The right answers were randomly varied between A and B throughout the test. Besides, for each brand name question, there were 20 choices (1 to 20) which include 10 target brand names and 10 foils of similar brand names. For each category, the right answers were different for every brand name question and randomly varied between odd (1, 3, 5, etc.) and even (2, 4, 6, etc.) choices throughout the test. Figure 3 shows examples of recognition-test questions. All the questions can be found in the Appendix C. Figure 3. Examples of PowerPoint slides used in the recognition test
The Shock Impact: An investigation of attitudes towards the use of shock tactics in charity advertisements.
While the use of shock has been praised for increasing attention, it has also been shown to cause distress and negatively affect the perception of the organization or brand. The use of shock advertising is increasingly popular in the non-profit sector, with organizations using shocking visual imagery to encourage viewers to take action against a cause or increase donations. This study aimed to deepen our understanding of attitudes held towards the effectiveness of this, and uncover attributes that contribute to this. Based on previous research into the effects of gender on advertisement preferences, we also analysed the opinions of male and female participants to unearth preferences for shocking or non-shocking advertisements. Three focus groups were conducted to collect attitudes towards charity advertisements. Participants were presented with six advertisements, split into three categories of health, animal, and child-based charities, each with one shocking and one non-shocking campaign. To compare genders, one focus group contained only males, one only female, and one mixed. It was found that the effectiveness of shock was perceived as higher for health related causes, lower for children’s charities, and mixed for animal causes. There was a difference between males and females in attitudes towards the use of shock in animal based charities, with females engaging more with the non-shocking advertisement, and males with the shocking. Results from this research improve our knowledge of when and why shock should be used in charity advertisements, how it can be used to target certain audiences.
Participants Sixteen participants were used in this study, consisting of students attending Lancaster University, with an age range from 20 to 28 years old. The sample had a majority of native speakers (13), with two Romanian and one Panamanian native speaker (English as second language). Participants were collected through opportunity sampling and took part in the study voluntarily. This study received departmental approval before data collection commenced. Design The study consisted of three focus groups: one containing only females (FGF), and one of only males (FGM) to examine any differences in attitudes between genders, and one of mixed gender (FG1) in order to assess possible conflicting attitudes within the group. Five students participated in the mixed focus group (three males, two females), five students in the female focus group, and six in the male focus group. Focus groups were conducted in a private room and lasted 40-50 minutes. Materials The stimuli presented to participants were of existing advertising campaigns released by non-profit organizations in the United Kingdom and United Sates of America. Three ‘non-shocking’ advertisements and three ‘shocking’ advertisements were chosen, with one centered around health, animal cruelty, and child abuse in both categories (Appendix A). ‘Shocking’ advertising has been defined by Dahl and colleagues (2003) as something that violates the social norm, including content that is seen as disgusting, obscene, vulgar, morally offensive, or containing sexual references. Using this definition as a guide, the ‘non-shocking’ advertisements were chosen dependent on the lack of these traits and did not include, for example, references to blood or death, obscene gestures, or violence. Adverts released by the National Society for the Prevention of Cruelty to Children (NSPCC), the National Health Service (NHS), and Battersea Dogs and Cats Home were chosen. Again, using this definition, we selected ‘shocking’ advertisements for their inclusion of the following shocking traits outlined by Dahl and colleagues (2003). Barnardo’s children’s charity was chosen for it’s obscene image of a distressed newborn baby with a Methylated Spirit bottle in its mouth. The Public Health Service’s Smoke Free advertisement featuring a cigarette that morphs into bloodied guts and tissue was chosen for its disgusting imagery. Lastly, People for the Ethical Treatment of Animals’ (PETA) ad featuring a dead, skinned animal was chosen due to its use of offensive images of harmed animals. These were printed out and presented to the participants on paper so they could have a closer look at the advertisements. A discussion guide was created to direct the conversation in the focus groups (Appendix B). The guide was designed so to ensure continuity between the groups as advised by Malhotra (2008), helping to tailor the discussion to the topics of the research aims, while also giving participants the opportunity to express their thoughts freely. Following Goulding’s (1998) guidelines, this discussion guide was flexible, enabling the facilitator to ask further questions in relation to what was brought up in conversation. Procedure Participants were seated around a table and had access to refreshments throughout the focus group. They were given time at the beginning to get comfortable and talk with fellow participants. Each participant was given an information sheet (Appendix C) that detailed the aims of the research and what they were expected to do. They were informed that they could ask any questions they wish and had the right to withdraw at any point during or after the focus group. Once they had read the information sheet and understood what they were talking part in, participants signed the consent form (Appendix D) to agree to take part in the study. At this point they were informed that the recording would commence. The discussion guide was followed throughout, firstly introducing the topic area that was being covered by the focus group, and encouraging participants to consider advertising in general. Following this they were asked about specifically charity advertisements and any overall feelings they had towards any they have seen. Participants then discussed the advertisements presented to them. Starting with the non-shocking advertisements, participants had time to view and discuss each advert one at a time, where they were asked about its effectiveness and anything they liked or disliked about them. The definition of ‘shocking’ advertisements was then introduced and the procedure was then repeated with presenting one advertisement at a time. Participants were then asked to compare their thoughts on which advertising tactic they thought was more effective and if there was a difference in this between the types of causes that were being advertised and the action that was being asked of the audience, for example a donation or change in behavior. This was done in the same order throughout the groups to ensure consistency across the groups. Lastly any final thoughts from the group were collected and participants were informed that they could email the investigator with any further thoughts they had if they wished. They were thanked for their participation and given a debrief sheet (Appendix E) containing more information of this research into the topic area as well as the contact details of the researcher and supervisor. The recording was then transcribed, and analysed thematically through the use of NVivo qualitative data analysis software, to highlight common themes throughout all three focus groups. This enabled us to compare attitudes held towards the varying types of advertising campaigns, their causes, and any differences between genders. Analysis The transcript for each focus group was entered into NVivo (QSR International Pty Ltd. Version 12, 2017) in preparation for thematic analysis. This was designed to uncover themes throughout the focus groups in a systematic way, identifying patterns found in the opinions of the participants. In order to accurately analyse the data, the thematic guidelines proposed by Braun and Clarke (2006) were followed. The transcripts were firstly read thoroughly to ensure a level of familiarity with the conversations. They were then coded in NVivo according to their content through an inductive approach, forming codes from the data at present as opposed to attempting to fit pre-existing framework by past theories, therefore allowing us to broaden our inclusion of the attitudes recorded. The data collected in these codes were sorted into potential themes, ensuring consistency within and variation between the themes. These themes were then re-analysed, making sure they were reflective of the data collected. The final themes were then decided upon.
Prospect theory and intermediate audience: the effects of context on behavioural intention
Prospect theory, gain/loss framing, intermediate audience, communication research, health communication, vaccination
Prospect theory predicts how people react to gain or loss-framed outcomes in dilemma situations, where the potential consequence of the choice is framed as a gain (e.g., lives saved) or as a loss (lives lost). This gain-loss framing communication strategy, derived from the theory, has been applied in many contexts, from promoting the use of reusable coffee mugs to vaccination compliance, with loss-framed appeals being found generally to be more persuasive than gain-framed appeals in the context of promoting vaccination. The current study focused on exploring whether these well-established effects persist when an intermediate audience is exposed to gain/loss-framed messaging, using influenza (flu) vaccination intentionality as an outcome. Intermediate audiences refer to those who are evaluating the gains and losses from the message on behalf of someone else (the ultimate audience), while normal audiences are those making decisions on their own behalf. Two hundred participants were recruited for an online, between-subject study, in which participants were split into two audience conditions and within which they were further split to view a gain-framed or a loss-framed message. Their subsequent behavioural intentions were measured as the outcome, with age as a potential moderating factor (and emotional attachment as a potential mediator exclusively for the intermediate audience condition). Results indicate that neither age nor emotional attachment are significant moderators or mediators. Loss-framed appeal enjoyed a persuasive advantage over the gain-framed appeal only in the intermediate audience condition. Possible interpretations of results, along with potential further directions of research, are discussed.
To test the outlined hypotheses, our current study took the form of an online Qualtrics questionnaire (see appendix B for questions) where the questionnaire would introduce participants to one of the audience conditions and view the appropriate version of the manipulated message before moving on to answering some items measuring their behavioural intention and emotional attachment. The study has a 2 (intermediate/normal audience condition) X 2 (gain/loss-framed appeal) design with emotional attachment as a potential mediating variable for the intermediate audience condition and behavioural intention as the outcome variable for all audience conditions. Participants We recruited 200 healthy adults based in the UK on Prolific, an online research participant recruitment platform. Participants have provided consent and completed the study remotely with their personal devices. Their unique Prolific ID was used in this study as the only identifier, which cannot be traced back to them personally. Participants were compensated monetarily for their participation. We randomly assigned our participants to one of the four audience conditions with 50 participants each: the normal gain-framed condition, the normal loss-framed condition, the intermediate gain-framed condition, and the intermediate loss-framed condition. Questionnaire design Consent The participant gave consent to participate in the study with the Qualtrics consent element so that participants can check a box for each item. There were seven items that the participants had to check one by one before commencing the study. Responses which failed to provide a full response in the consent item would be removed from the study. Demographics For demographics, we have recorded the participants' age and gender for the records. As mentioned, age was also analysed as a moderator as part of our analysis. We have also recorded their Prolific IDs to ensure completion and arrange payment. Settings of the study After giving demographic information, participants were introduced to a small piece of information that gave them the context of this study. In normal audience conditions, participants were told that someone had sent them an ad about the flu vaccination, which refers to the manipulated message they will soon view. While for the intermediate audience, on top of the information that is revealed to the normal audience, they were exclusively told that they were a manager in a small town's paper company, which gives them the role of an intermediate audience (manager) who must evaluate the later presented message on behalf of other parties (employees) with themselves irrelevant to the gains and losses. Material We have chosen flu vaccination as our topic malady for the manipulation messages as COVID vaccines, as used in recent studies, are perhaps less relevant in what is generally thought of as the post-COVID era. Flu vaccinations, unlike many other vaccines, remain relevant to the major population and most age groups. To allow a closer resemblance to real-world settings and increase the generalisability of the results, we have made unofficial Facebook posts that claim to be from the NHS as the message format. Participants were informed that the graphics were not an actual Facebook post from the NHS but rather a material used solely for this study. See Figure 2 for an example, and appendix A for the complete set of stimuli presented to the participants in the study. Audience condition. Figure 2 is the gain-framed version of the message from the normal audience condition. In normal audience conditions, the message communicates directly to the participants, stating the potential pros or cons for the participants when the participants decide to vaccinate or not vaccinate. In this condition, it is assumed that the participants evaluated the message on their behalf and nobody else's. While on the contrary, the intermediate audience condition communicates a slightly different message. The "you" in the message is replaced by "your employees". The purpose of this is to highlight that the participants evaluate this message as an intermediate audience (the manager), deciding whether they would recommend the vaccine to somebody else (the ‘ultimate audience’) given the outlined potential gains and losses, while the gains and losses remain irrelevant to the participants personally. Message framing. The figure is a gain-framed message, and as mentioned, it follows the logical flow of "if you vaccinate, good things will happen". As we can see in Figure 2, if the recipient vaccinates, then according to the text, he/she would have a reduced chance of infection and a reduction in the duration and severity of the symptoms. The lost-framed version of the message follows the logical flow of "if you do not vaccinate, bad things will happen." So, in contrast to figure 2, the lost framed messages would say if the recipient does not vaccinate, he/she would have an increased chance of infection and increase in duration and severity of the symptoms. The two messages communicate the same reality and are logically equivalent. Hence, any differences between the groups can be attributed to the message framing. Check questions. After viewing the message, the participants were asked two questions regarding the ads content before moving on to later questions. The check questions were designed to be simple reading comprehension questions that check whether the participants attended to the message in the reading process. We have removed all responses failing to provide a correct answer in either one of the questions. Behavioural intention After viewing the framed messages, we have several Likert scale 7-point agree-disagree items used to measure the behavioural intention of the participants. However, given the audience condition differences and hence the potential differences in the decision-making process, behavioural intention for the two types of audience is defined differently. For the intermediate audience condition, behavioural intention is defined as "the intention to recommend/promote behaviour to the ultimate audience (employees)". While for the normal audience conditions, we measure their intention to get the vaccination for themselves. Both audience conditions responded to six items probing their behavioural intentions. In the normal audience condition, participants were asked how likely they would be to get the flu jab, how urgent they thought it is, and whether they would likely plan to get a flu jab after viewing the message. There are also items with reversed wordings asking whether they think getting a flu jab is NOT urgent. The intermediate audience was asked how likely they are to recommend the flu vaccine to their employees and how urgent and necessary they believe the vaccine is to their employees. (See the appendix for the complete set of questions.) Emotional attachment As mentioned, there are speculations revolving around the involvement of relational dynamics and relevant emotions in the intermediate audience. Therefore, we have arranged a set of questions probing the participant's emotional attachment towards the employee exclusively for the intermediate audience condition. There were four questions in total in this part of the study, which focused solely on the participants' sense of protection towards the employee, asking to what extent the participants thought that the vaccine was necessary for the employee's own good and well-being, and to what extent were the participants eager to protect them; an item with reversed wordings were also included. (See the appendix for the complete set of questions.) Method of analysis We analysed the data using the clm() and clmm() functions from the ordinal package in RStudio using R version 4.1.1. We first confirmed the main effects of message framing and audience conditions using clm(), and then we moved on to analyse the magnitude of random interacting effects of age, question type and individual differences. The reason for choosing cumulative link models (clm) was that the models were designed explicitly for ordinal variables like Likert scales, which predict the probability of each response level, unlike some metric models and prevent type 1 and type 2 errors resulting from forcing ordinal variables onto metric models (Liddell & Kruschke, 2018). As for emotional attachment, given each item was probing quite a different emotion (e.g., sense of responsibility/ sense of protection), we have decided to fit a multivariate ordinal variable using the mvord() function to see if there is a significant difference in the multiple emotional outcomes under different audience condition, after which we investigated if any emotional attachment item was a significant predictor of behavioural intention using another clm model. We have also fitted clm() models including the interaction term between age and conditions predicting behavioural intention to see if age moderates the relationship between message framing and behavioural intention as proposed. Lastly, we have fitted a cumulative link mixed model (clm) to consider the role of potential sources of random effects such as participant differences and question differences in the analyses.
Eleanor Little, Alicia Turner, Laurie Dixon
Data/Excel.csv Analysis/r_file.R Text/Word.doc
The Decoy Effect on Choosing Branded and Non-Branded Alcohol-related Products
The decoy effect describes a phenomenon that the introduction of a third choice, usually an asymmetrically dominated one, would change the distribution of people’s preferences for the original two options. Monk et al. (2016) found a basic decoy effect on alcohol purchasing decisions. Extending this, the current study examined the impact of the decoy effect on alcohol-related purchasing decisions and whether the addition of brand names would further impact this. A total of 106 participants were asked to make decisions amongst four types of branded and unbranded drinks by completing an online questionnaire. They also completed the AUDIT, assessing problem drinking patterns, and a measure of trait effortful control. Results showed that the decoy appeared to affect alcoholic relative to non-alcoholic drinks, and affected branded products more than non-branded products. The results suggest that the decoy effect might affect alcohol-related purchasing decisions differently to non-alcoholic purchasing decisions, which might have managerial implications for marketers and health implications for hazardous alcohol consumptions.
All the stimuli were pictures of bottles presented with text descriptions including the number of bottles and the total prices. Participants viewed a total of 80 deals, with 40 alcoholic products and 40 non-alcoholic products. Half of the products were branded and half unbranded. With regards to branded stimuli, pictures of bottles similar to those presented in supermarkets were shown (see Figure 2), whilst unbranded ones used similar unbranded bottles in terms of colour and shape. This allowed the products to correspond with both the diversity of goods in real supermarket but also to avoid unnecessary brand association (e.g. red glass bottles always remind consumers of Coca-Cola; Underwood, 2003). In the control condition, participants were shown products with two options, one with less bottles but cheaper, and the other with a greater quantity of bottles but more expensive. As such, option 1 represented the competitor option, which was cost-effective, and option 2 represented the target option, which was moderately cost- effective. The order of cost-effective and moderate-cost effective products was randomised throughout the experiment. In comparison, the experimental conditions also included a decoy option, which presented a product that was the least cost-effective. Although the decoy option itself was unlikely to be selected, it was expected to result in a different distribution of selections from the output of the control group. The sequences of the choice A (cost-effective), B (moderate cost-effective), and the C (decoy) were set randomly. Alcohol Use Disorders Identification Test (AUDIT). This questionnaire was made up of 10-items concerning personal drinking habits, drinking frequency and amount (Saunders et al., 1993). On a scale of one to over 30, articipants responsed to the questions such as “How many units of alcohol do you drink on a typical day when you are drinking?” and a total AUDIT score was computed. The scores of each question were accumulated and coded. The output of the AUDIT test showed great reliability of this study, M = 15.09, SD = 4.60, Cronbach’s α = .79. It should be noted that although the figure for the AUDIT test was way above eight which was the hazardous cut-off, indicating a possible harmful alcohol use (Babor et al., 2001), this was in line with student’s drinking cultures in UK. Adult Temperament Questionnaire (ATQ). This questionnaire assessed self-reported effortful control (c.f., Evans & Rothbart, 2007) and comprised of 34-items, such as “When interrupted or distracted, I usually can easily shift my attention back to whatever I was doing before”. Participants were asked to answer the questions by selecting a 7-point Likert Scale (1 = extremely untrue, 7 = extremely true). Their responses were recorded and coded. A small amount of missing data (caused by unexpected errors on the web) was replaced by the mean of the sample on that specific item. The result of the ATQ test revealed internal consistency as well, M = 146.34, SD = 22.82, Cronbach’s α = .85. Design and Procedure This study conducted a 4 Stimuli (Beer, Cider, Orange Juice and Water) x 2 Brading (Branded vs unbranded) x 2 Selection (Cost-effectiveness vs. Moderate Cost-effectiveness) within-subjects research design, to examine the possible shifts of selections with the addition of the decoy. Participants were instructed to look at online supermarket choice sets and asked to make a choice out of two (control condition) of three product options (the experimental condition, with the decoy product added). At the beginning, they were asked to imagine that they were in a real supermarket, and they were told that their selections would be dependent on their own preferences. No other information was provided either in oral or on the screen in order to prevent demand characteristics. The main questionnaire had 80 questions, consisting of 80 trials of stimuli (i.e., 20 trials for beer, water, orange juice, and cider). Also 40 groups of bottles were branded and the other 40 were non-branded. The main questionnaire comprised four web pages, with 20 questions in each page and took approximately 30 minutes to complete. Participants were allowed to take short breaks when they finished one page of questions. There was no time limit for each of the questions as the pressure caused by time constraints has been found to affect one’s decision-making process (Dhar & Nowlis, 1999). Subsequently, participants completed a self-report measure of hazardous drinking behaviour (AUDIT) and the effortful control scale (ATQ). These questionnaires were completed at the end of the experiment to make sure the alcohol-related behaviours were not primed (Monk et al., 2016). At the end of the experiment, participants completed a manipulation check to ensure that they were able to accurately distinguish the cost-effectiveness and the quantity of the products set and that they fully understood the requirements of this study. They were then asked to report if they had consumed alcohol on the day of testing, as alcohol consumption has been shown to affect decision-making and may therefore affect the findings of the experiment (Steele & Josephs, 1990). Therefore, participants who had consumed alcohol before participating in the test were excluded when analysing the decoy effect (n = 8). Finally, participants were fully debriefed after they had finished the whole experiment, and were informed about the true aims and hypotheses of the study.
Exploring the impact of rewards on contextual cueing effect
contextual cueing effect, reward, selective attention
There is a huge amount of complex information about visual stimuli in the environment and the individual's visual processing system has a limited capacity to process this information, so selective attentional mechanisms prioritise the most valuable information. Fixed contextual cues in the environment help us to allocate attentional resources efficiently. In their study of context, Chun and Jiang proposed a contextual cueing effect (CC effect). This effect is likely to be an implicit learning resulting from selective attention. Specifically, subjects searched for the target faster in the repeated configuration than in the random configuration, as fixed contextual cues would help locate the target. It was found that this effect could be moderated by manipulating external motivation, i.e., reward. However, there is so far considerable debate as to whether high rewards can contribute to the cc effect, and whether rewards act on the cc effect or on the positional probability learning effect. The present experiment used a classical situational cueing task and a mixed between-*within group experimental design to explore the effect of reward on the contextual cueing effect. The experimental results show that high rewards did not contribute more significantly to the cc effect than low rewards, but high rewards did facilitate the target probability learning effect.
Participants Fifty-two Lancaster University students (20 identified as male and 32 as female; age M=23.9, SD=2.55 years, range: 19-33 years) participated in the experiment. Two participants were excluded from the final analysis (see below for details). All participants had normal or corrected normal vision. Participants were informed that the three participants with the highest scores in the experiment would receive a £20 Amazon voucher as a reward. At the end of the experiment, the three participants with the highest scores had received their £20 Amazon vouchers by e-mail. The experiment passed ethical review by the Department of Psychology at Lancaster University. All participants were shown a participant information sheet and signed a consent form to participate in this study prior to the start of the experiment. The Participant Debrief Sheet was presented to participants at the end of the experiment. Materials The materials were created and presented with the Psychophysics Toolbox Version 3 (Brainard, 1997) MATLAB (MathWorks, Sherborn, MA) toolbox. The stimuli were displayed on an MS-Windows machine on a screen with 1920 × 1080 pixels resolution and 60 Hz refreshing rate. Each display consists of 11 L-shaped and one T-shaped black 1.25° x 1.25° items, presented on a white background. The only T-shaped item in each display is the target, which has a 90° rotation clockwise (called left) or counterclockwise (called right). There were an equal number of times that the target was rotated to the left as it was rotated to the right across the experiment. The L-shaped distractors were randomly rotated by 0°, 90°, 180° or 270°. To increase the difficulty of the task (Jiang & Chun, 2001), the L-shaped items had a 4-pixel offset at the junction of the lines to make them similar to the T-shaped targets. In each display, all items were balanced within the quadrant of the display. This randomisation was carried out for each subject individually. Experiment design This experiment was conducted in a quiet testing room, with each subject alone in the room to complete the experiment. The experiment consisted of 20 training blocks. Each block consisted of 16 trials. Each trial began with a 0.5 second fixation cross, followed by a search display until the subject's manual response or reached the maximum response time limit of 6 seconds. Participants were asked to respond as quickly and accurately as possible, reporting the direction of the target by pressing C or N on the standard keyboard numeric keypad, respectively ("T" stems pointing left or right). Each of the 5 training blocks was divided into one epoch, for a total of four epoch, with subjects having a fixed 30 second rest period between epochs. The whole experiment will last about 40 minutes. Participants will be given a score (points) after each test based on their reaction time (correct response within 2 seconds), i. e. the 'reward' for the experiment. Each subject is informed before the experiment that they will have a final score at the end of the experiment and that the top three participants with the highest scores will receive a £20 voucher. The experiment will use two reward conditions, a high (score*10) and a low (score*1) reward. In the high reward condition, the correct answer will be scored as (2000 - reaction time) *10. In the low reward condition, the correct answer will be scored as (2000 - reaction time) *1. For each subject, eight positions in the imaginary ring were randomly selected as target positions. Each quadrant had an equal number of target positions. In each block, each target location was presented once in a repeated display and once in a new display in the same reward condition (twice in total). In the repeated display, the position and orientation of the distractor remained constant along with the target position, while in the new display both were changed randomly. In both the new and repeated displays, the target orientation was changed randomly so that no link could be made between the repeated configurations, target locations or reward values and specific responses. The eight target positions were divided into two different categories: (1) four target positions were always combined with a high reward (score*10) in both repeated and new displays; (2) the other four target positions were always combined with a low reward (score*1) in both repeated and new displays. Therefore, the configurations in the repeated trials were also only ever paired with high or low rewards. A mixed experiment design was used in this study, with the within-subjects factor being the feedback received after the subjects' responses. During the feedback phase of each trial, the score obtained for this experiment is displayed on the screen if the correct response is received within a time window of 2 seconds from the start of the display. The screen will also display whether this trial is a "10x bonus" one or a "normal trial". For trials with a correct response time of more than 2 seconds, no score is awarded, and the feedback is "too slow, 0 points" displayed in the centre of the screen. For trials with a reaction time of more than 6 seconds, 10,000 points will be deducted, and the feedback will be "Time out! Too slow, -10,000 points". For incorrect responses, 10,000 points will be deducted, and the feedback will be "Error! -10,000 points". The total number of points accumulated so far will be displayed below the feedback 1 second after feedback is presented. This experiment also had a between-subjects design in which subjects were randomly divided into two groups, with the odd-numbered participants being the “instructed group”, and those in the instructed group will see a prompt in the centre of the screen before the start of each trial, informing them that the trial is a high or low reward condition. For the high reward condition, "10x BONUS trial!" will be displayed in the centre of the screen in green. For the low reward condition, "Normal trial" will be displayed in the centre of the screen in white. Participants in the even numbered group are in the "not instructed group". Subjects in the “not-instructed group” will not see a prompt in the centre of the screen before the start of each trial and will only see if they have received 10x the reward for their score during the feedback phase.