Exploring negativity bias in brand beliefs and stated brand switching propensity

Negativity bias has been well studied by psychologists but limited research has been conducted on it in a marketing context. Given previous research, this exploratory study aims to examine whether there are any negativity bias effects in brand beliefs and whether there is any influence on stated brand switching propensity amongst current users of a brand. The results suggest that there is a negativity bias evident in brand image data.

社会冲突信息加工的事件相关电位研究

Processing of discrepant information is an important part in our everyday life. According to the social attributes of information, it can be categorized into two parts: social discrepancy and nonsocial discrepant information. The researches focused on nonsocial discrepancy are much mature than those of social discrepancy processing. This serial study employed three ERP experiments to explore the attributes of social discrepancy cognition. Experiment one compared the ERP differences between social and nonsocial discrepancy processing, experiment two adopted single stimulus paradigm to explore the negativity attention biases of social emotions, experiment three investigated the affective mechanism of emotions to social discrepancy information with cue-target paradigm, based on the experiment one and two. We invited healthy undergraduates to participate in our researches, in which social gender words and affective images were stimuli to explore the temporal sequences, activated modes and affective mechanisms of social discrepancy. The results were as below: 1. The differences of attention resource distributions between social and nonsocial information processing exhibited as early as 200 ms, since which P2 was evoked in both blocks. The larger P2 in nonsocial block represented the more attention to physical and nonsocial attributes of objects. N300/400 indicated the differences of evaluating systems in each block. The cognitive mechanisms of social and nonsocial tasks were specific, based on the fact: (1) the discrepancy evaluating system was activated earlier in nonsocial block than that of social block; (2) the social cognition performed right hemisphere advantage, but nonsocial task did not so. 2. Social emotions also could raise a negativity bias on attention. The latency of P2 evoked by social sad images was shorter than that of social happiness and neutral images. The latencies of P2 indicated that sad emotions attracted attention earlier, and possessed a processing advantage. The phenomenon that the larger N2 was evoked by social sadness showed that people was easily moved by sad emotions and sympathized the sadness. 3. Emotions affected social discrepancy processing. Positive affective mood magnified the discrepancy effect, based on the smaller latencies of difference N400 and larger amplitudes. Persons with happy mood synthesized social stereotypes to accelerate the social tasks. 4. Three experiments all showed the right hemisphere advantages of social cognition and social emotions, offered more proof in laterality hypothesis of social cognition. Above all, social cognition had essential distinctions with nonsocial cognition; they two had their own specific characteristics. The fact that social cognition was prone to be affected by different emotional mood made it more complex.

Traitement cérébral de sons émotionnels : une perspective électrophysiologique

Des sons émotionnels furent présentés comme stimuli cibles lors d'une tâche auditive de type oddball. Les effets acoustiques furent départagés des effets émotionnels à l'aide d'une tâche contrôle similaire utilisant une version brouillée des sons originaux et dépourvue de propriétés émotionnelles. Les résultats du oddball émotionnel qui ont différé du oddball contrôle ont montré des effets de valence inversés dans les composantes électrophysiologiques P2 et P300; la valence négative ayant une amplitude plus grande dans la fenêtre de 130-270ms mais moins intense autour de 290-460ms, lorsque comparée aux valences positives et neutres. Les résultats P2 peuvent être interprétés comme une mobilisation attentionnelle précoce privilégiant les stimuli potentiellement dangereux, tandis que les résultats de la P300 pourrait indiquer une évaluation moins détaillée de ces stimuli.

The time course of implicit affective picture processing: an eye movement study

Consistent with a negativity bias account, neuroscientific and behavioral evidence demonstrates modulation of even early sensory processes by unpleasant, potentially threat-relevant information. The aim of this research is to assess the extent to which pleasant and unpleasant visual stimuli presented extrafoveally capture attention and impact eye movement control. We report an experiment examining deviations in saccade metrics in the presence of emotional image distractors that are close to a nonemotional target. We additionally manipulate the saccade latency to test when the emotional distractor has its biggest impact on oculomotor control. The results demonstrate that saccade landing position was pulled toward unpleasant distractors, and that this pull was due to the quick saccade responses. Overall, these findings support a negativity bias account of early attentional control and call for the need to consider the time course of motivated attention when affect is implicit

Subjective Ambivalence and the Expression of Anti-Gay Bias

Univalent attitudes toward gay people have been widely studied, but no research to date has examined ambivalent (i.e., torn, conflicted) attitudes toward gay people. However, the Justification-Suppression Model (JSM; Crandall & Eshleman, 2003) proposes that ambivalence leads to biased expressions through intrapsychic processes which facilitate biased expression, particularly in contexts presenting strong justifications for expressing prejudice and weak pressures to suppress prejudice. I test these implications in the context of bias toward gay people. In Study 1, the measurement of ambivalence is examined in terms of both subjective ambivalence (i.e., the reported experience of “torn” attitudes) and calculated ambivalence (i.e., mathematical conflict between positive and negative attitude components). I find that higher subjective ambivalence is only associated with more negative attitudes toward gay people (and not positive attitudes toward gay people), and that higher subjective ambivalence predicts less gay rights support even after taking negative and positive attitudes toward gay people into account. Further, higher subjective ambivalence is associated with ideological opposition to gay people and more negative intergroup emotions (e.g., intergroup disgust). These findings suggest it is valuable to examine the unique component of subjective ambivalence separate from univalent negativity. Because calculated ambivalence measures are mathematically dependent upon a univalent negative measure, they cannot be examined separately from negativity. Therefore, subjective ambivalence is the focus of Study 2. The main goals of Study 2 were to determine why and when subjective ambivalence is related to bias. I examined the extent to which the negative relation between subjective ambivalence and opposition to anti-gay bullying can be accounted for by lower intergroup empathy and lower collective guilt, which may facilitate the expression of bias in keeping with the JSM. The relation between subjective ambivalence and anti-gay bullying opposition was examined within four social contexts based on a 2 (high vs. low offensiveness) x 2 (normatively unjustified vs. normatively justified) manipulation. I expected that higher subjective ambivalence would be most strongly related to lower intergroup empathy and collective guilt when there are the strongest justifications for bias expression, and that lower intergroup empathy and collective guilt would lead to less opposition to anti-gay bullying. Higher subjective ambivalence predicted less anti-gay bullying opposition. After accounting for positivity and negativity, the direct effect of subjective ambivalence was no longer significant, yet subjective ambivalence uniquely predicted intergroup empathy, which in turn predicted less anti-gay bullying opposition. These findings provide evidence that subjective ambivalence is largely negative in nature, but also presents evidence for a unique component of subjective ambivalence (separate from univalent attitudes) associated with low intergroup empathy and negativity. In contrast to previous research, I found very little evidence for the context-dependency of subjective ambivalence. Further research on subjective ambivalence, including subjective ambivalence toward other social groups, may expand our understanding of the factors leading to biased expressions.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

Error, Bias, and Long-Branch Attraction in Data for Two Chloroplast Photosystem Genes in Seed Plants

Sequences of two chloroplast photosystem genes, psaA and psbB, together comprising about 3,500 bp, were obtained for all five major groups of extant seed plants and several outgroups among other vascular plants. Strongly supported, but significantly conflicting, phylogenetic signals were obtained in parsimony analyses from partitions of the data into first and second codon positions versus third positions. In the former, both genes agreed on a monophyletic gymnosperms, with Gnetales closely related to certain conifers. In the latter, Gnetales are inferred to be the sister group of all other seed plants, with gymnosperms paraphyletic. None of the data supported the modern ‘‘anthophyte hypothesis,’’ which places Gnetales as the sister group of flowering plants. A series of simulation studies were undertaken to examine the error rate for parsimony inference. Three kinds of errors were examined: random error, systematic bias (both properties of finite data sets), and statistical inconsistency owing to long-branch attraction (an asymptotic property). Parsimony reconstructions were extremely biased for third-position data for psbB. Regardless of the true underlying tree, a tree in which Gnetales are sister to all other seed plants was likely to be reconstructed for these data. None of the combinations of genes or partitions permits the anthophyte tree to be reconstructed with high probability. Simulations of progressively larger data sets indicate the existence of long-branch attraction (statistical inconsistency) for third-position psbB data if either the anthophyte tree or the gymnosperm tree is correct. This is also true for the anthophyte tree using either psaA third positions or psbB first and second positions. A factor contributing to bias and inconsistency is extremely short branches at the base of the seed plant radiation, coupled with extremely high rates in Gnetales and nonseed plant outgroups. M. J. Sanderson,* M. F. Wojciechowski,*† J.-M. Hu,* T. Sher Khan,* and S. G. Brady

Attention and memory bias for body image and health related information using an Emotional Stroop task in a non-clinical sample

It has been proposed that body image disturbance is a form of cognitive bias wherein schemas for self-relevant information guide the selective processing of appearancerelated information in the environment. This threatening information receives disproportionately more attention and memory, as measured by an Emotional Stroop and incidental recall task. The aim of this thesis was to expand the literature on cognitive processing biases in non-clinical males and females by incorporating a number of significant methodological refinements. To achieve this aim, three phases of research were conducted. The initial two phases of research provided preliminary data to inform the development of the main study. Phase One was a qualitative exploration of body image concerns amongst males and females recruited through the general community and from a university. Seventeen participants (eight male; nine female) provided information on their body image and what factors they saw as positively and negatively impacting on their self evaluations. The importance of self esteem, mood, health and fitness, and recognition of the social ideal were identified as key themes. These themes were incorporated as psycho-social measures and Stroop word stimuli in subsequent phases of the research. Phase Two involved the selection and testing of stimuli to be used in the Emotional Stroop task. Six experimental categories of words were developed that reflected a broad range of health and body image concerns for males and females. These categories were high and low calorie food words, positive and negative appearance words, negative emotion words, and physical activity words. Phase Three addressed the central aim of the project by examining cognitive biases for body image information in empirically defined sub-groups. A National sample of males (N = 55) and females (N = 144), recruited from the general community and universities, completed an Emotional Stroop task, incidental memory test, and a collection of psycho-social questionnaires. Sub-groups of body image disturbance were sought using a cluster analysis, which identified three sub-groups in males (Normal, Dissatisfied, and Athletic) and four sub-groups in females (Normal, Health Conscious, Dissatisfied, and Symptomatic). No differences were noted between the groups in selective attention, although time taken to colour name the words was associated with some of the psycho-social variables. Memory biases found across the whole sample for negative emotion, low calorie food, and negative appearance words were interpreted as reflecting the current focus on health and stigma against being unattractive. Collectively these results have expanded our understanding of processing biases in the general community by demonstrating that the processing biases are found within non-clinical samples and that not all processing biases are associated with negative functionality

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.