Response efficacy : the key to minimizing rejection and maximizing acceptance of emotion-based anti-speeding messages

This study sought to improve understanding of the persuasive process of emotion-based appeals not only in relation to negative, fear-based appeals but also for appeals based upon positive emotions. In particular, the study investigated whether response efficacy, as a cognitive construct, mediated outcome measures of message effectiveness in terms of both acceptance and rejection of negative and positive emotion-based messages. Licensed drivers (N = 406) participated via the completion of an on-line survey. Within the survey, participants received either a negative (fear-based) appeal or one of the two possible positive appeals (pride or humor-based). Overall, the study's findings confirmed the importance of emotional and cognitive components of persuasive health messages and identified response efficacy as a key cognitive construct influencing the effectiveness of not only fear-based messages but also positive emotion-based messages. Interestingly, however, the results suggested that response efficacy's influence on message effectiveness may differ for positive and negative emotion-based appeals such that significant indirect (and mediational) effects were found with both acceptance and rejection of the positive appeals yet only with rejection of the fear-based appeal. As such, the study's findings provide an important extension to extant literature and may inform future advertising message design.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

The role of emotion in product, service and business model design

Designers have become aware of the importance of creating strong emotional experiences intertwined with new tangible products for the past decade, however an increased interest from firms has emerged in developing new service and business models as complimentary forms of emotion-driven innovation. This interdisciplinary study draws from the psychological sciences – theory of emotion – and the management sciences – business model literature to introduce this new innovation agenda. The term visceral hedonic rhetoric (VHR) is defined as the properties of a product, (and in this paper service and business model extensions) that persuasively induce the pursuit of pleasure at an instinctual level of cognition. This research paper lays the foundation for VHR beyond a product setting, presenting the results from an empirical study where organizations explored the possibilities for VHR in the context of their business. The results found that firms currently believe VHR is perceived in either their product and/or services they provide. Implications suggest shifting perspective surrounding the use of VHR across a firm’s business model design in order to influence the outcomes of their product and/or service design, resulting in an overall stronger emotional connection with the customer.

A comparison of dimensional models of emotion: evidence from emotions, prototypical events, autobiographical memories, and words.

The intensity and valence of 30 emotion terms, 30 events typical of those emotions, and 30 autobiographical memories cued by those emotions were each rated by different groups of 40 undergraduates. A vector model gave a consistently better account of the data than a circumplex model, both overall and in the absence of high-intensity, neutral valence stimuli. The Positive Activation - Negative Activation (PANA) model could be tested at high levels of activation, where it is identical to the vector model. The results replicated when ratings of arousal were used instead of ratings of intensity for the events and autobiographical memories. A reanalysis of word norms gave further support for the vector and PANA models by demonstrating that neutral valence, high-arousal ratings resulted from the averaging of individual positive and negative valence ratings. Thus, compared to a circumplex model, vector and PANA models provided overall better fits.

The Representation of Emotion in Autonomic and Central Nervous System Activity

Phenomenologically, humans effectively label and report feeling distinct emotions, yet the extent to which emotions are represented categorically in nervous system activity is controversial. Theoretical accounts differ in this regard, some positing distinct emotional experiences emerge from a dimensional representation (e.g., along axes of valence and arousal) whereas others propose emotions are natural categories, with dedicated neural bases and associated response profiles. This dissertation aims to empirically assess these theoretical accounts by examining how emotions are represented (either as disjoint categories or as points along continuous dimensions) in autonomic and central nervous system activity by integrating psychophysiological recording and functional neuroimaging with machine-learning based analytical methods. Results demonstrate that experientially, emotional events are well-characterized both along dimensional and categorical frameworks. Measures of central and peripheral responding discriminate among emotion categories, but are largely independent of valence and arousal. These findings suggest dimensional and categorical aspects of emotional experience are driven by separable neural substrates and demonstrate that emotional states can be objectively quantified on the basis of nervous system activity.

Teachers' and teacher educators' lives: the role of emotion

This paper reports research which focuses on ways of enhancing understandings by teachers of the key role that emotions play in their personal professional growth. It combines the narrative, autobiographical accounts of teachers attending part-time masters degree programmes in England (Continuing Professional Development and School Improvement) and Northern Ireland (Personal and Social Development) with an interrogation of the underlying values which affect the practices of their tutors. It reveals the effects of powerful and often unacknowledged interaction between personal biography and professional and social contexts upon teachers in schools and higher education.

Perception of emotion: towards a realistic understanding of the task

A decade ago, perceiving emotion was generally equated with taking a sample (a still photograph or a few seconds of speech) that unquestionably signified an archetypal emotional state, and attaching the appropriate label. Computational research has shifted that paradigm in multiple ways. Concern with realism is key. Emotion generally colours ongoing action and interaction: describing that colouring is a different problem from categorizing brief episodes of relatively pure emotion. Multiple challenges flow from that. Describing emotional colouring is a challenge in itself. One approach is to use everyday categories describing states that are partly emotional and partly cognitive. Another approach is to use dimensions. Both approaches need ways to deal with gradual changes over time and mixed emotions. Attaching target descriptions to a sample poses problems of both procedure and validation. Cues are likely to be distributed both in time and across modalities, and key decisions may depend heavily on context. The usefulness of acted data is limited because it tends not to reproduce these features. By engaging with these challenging issues, research is not only achieving impressive results, but also offering a much deeper understanding of the problem.

Emotional intelligence, personality and decoding non-verbal expressions of emotion

Previous research has highlighted theoretical and empirical links between measures of both personality and trait emotional intelligence (EI), and the ability to decode facial expressions of emotion. Research has also found that the posed, static characteristics of the photographic stimuli used to explore these links affects the decoding process and differentiates them from the natural expressions they represent. This undermines the ecological validity of established trait-emotion decoding relationships. This study addresses these methodological shortcomings by testing relationships between the reliability of participant ratings of dynamic, spontaneously elicited expressions of emotion with personality and trait EI. Fifty participants completed personality and self-report EI questionnaires, and used a computer-logging program to continuously rate change in emotional intensity expressed in video clips. Each clip was rated twice to obtain an intra-rater reliability score. The results provide limited support for links between both trait EI and personality variables and how reliably we decode natural expressions of emotion. Limitations and future directions are discussed.