Trajectories of university adjustment in the United Kingdom: Emotion management and emotional self-efficacy protect against initial poor adjustment

Little is known about individual differences in the pattern of university adjustment. This study explored longitudinal associations between emotional self-efficacy, emotion management, university adjustment, and academic achievement in a sample of first year undergraduates in the United Kingdom (N=331). Students completed measures of adjustment to university at three points during their first year at university. Latent Growth Mixture Modeling identified four trajectories of adjustment: (1) low, stable adjustment, (2) medium, stable adjustment, (3) high, stable adjustment, and (4) low, increasing adjustment. Membership of the low, stable adjustment group was predicted by low emotional self-efficacy and low emotion management scores, measured at entry into university. This group also had increased odds of poor academic achievement, even when grade at entry to university was controlled. Students who increased in adjustment had high levels of emotion management and emotional self-efficacy, which helped adaptation. These findings have implications for intervention

Emotion management as struggle in dirty work: the experiences of exotic dancers

We further the research to date on ambiguity, ambivalence and contradiction in organisation studies by integrating the dirty work and emotion management literatures. Our intent is to better understand the complex cognitive processes underpinning everyday experiences of those working in what has been perceived to be a high-breadth high-depth stigmatised occupation, that is, exotic dancing. Dancers’ stories reveal they are acutely aware of social and moral taint associated with the work and in turn their self-identities. They adopt a number of strategies to manage their spoiled identities and we contribute by unpicking the cognitive processes that underpin these strategies. In extending strategies of emotional ambivalence at work and stigma management, we conclude that through a lens of emotion management as struggle, exotic dancers, and more broadly dirty workers, do not ‘resolve’ the ambivalence, contradiction and ambiguity they confront but can be seen to experience at best a type of contingent coherence in their everyday work

Emotion management in small hotels: meeting the challenges of flexibility and informality

This paper shows that in small hotels, hotel owners interpret „hospitality‟ more broadly than mere commercial concerns. Hoteliers engage with three interdependent hospitality domains, commercial, social and private (Lashley, 2000), an approach that enables them to perceive guest interactions as informal; characterised by hoteliers wanting to „know‟ and „relate to‟ their guests. The findings here, drawn from a study of small hotels in the UK, show how owners manage this form of the „host-guest relationship‟ (Tucker, 2003) by employing a range of emotion management strategies. These mirror Bolton‟s 4Ps framework (2009) of pecuniary, professional, presentational and philanthropic emotion management roles. Adopting this fluid approach, rather than relying on emotional labour (Hochschild, 1983), enables the hoteliers to respond flexibly to meet the needs of their different types of guest. The findings in this paper validate Bolton‟s argument (2005) for using agential flexible emotion management that captures but goes beyond emotional labour

Contemplating Mindfulness at Work: An Integrative Review

Mindfulness research activity is surging within organizational science. Emerging evidence across multiple fields suggests that mindfulness is fundamentally connected to many aspects of workplace functioning, but this knowledge base has not been systematically integrated to date. This review coalesces the burgeoning body of mindfulness scholarship into a framework to guide mainstream management research investigating a broad range of constructs. The framework identifies how mindfulness influences attention, with downstream effects on functional domains of cognition, emotion, behavior, and physiology. Ultimately, these domains impact key workplace outcomes, including performance, relationships, and well-being. Consideration of the evidence on mindfulness at work stimulates important questions and challenges key assumptions within management science, generating an agenda for future research

Development of a single-session, transdiagnostic preventive intervention for young adults at risk for emotional disorders

Cognitive-behavioral prevention programs have demonstrated efficacy in reducing subclinical symptoms of anxiety and depression, and there is some evidence to suggest that they can lower the risk of future disorder onset. However, existing interventions tend to be relatively lengthy and target specific disorders or problem areas, both of which limit their potential for widespread dissemination. To address these limitations, we aimed to develop a single-session, transdiagnostic preventive intervention based on the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders for young adults at risk for developing anxiety and/or depressive disorders within a college setting. Results from this proof-of-concept study indicated that the intervention was viewed as highly satisfactory and acceptable. The intervention also was successful at delivering adaptive emotion management skills in its 2-hr workshop format. Future studies evaluating the efficacy of this novel transdiagnostic, emotion-focused prevention program are warranted.Accepted manuscrip

Emotional Intelligence Measured in a Highly Competitive Testing Situation

This is a study in which emotional intelligence (EI) as well as several other personality dimensions were studied in a real, high-stakes, selection situation, N=190. Forty-one trait oriented personality scales were measured and factor analyzed. A factor pattern with four secondary factors was found: EI, emotional stability, rigidity/perfectionism and energy/dominance. These factors were related to standard FFM (Five Factor Model) dimensions, to Hogan's Development Survey ("the dark side of personality") and to a number of tasks measuring skills in identifying emotions and emotion knowledge. It was found that EI and emotional stability correlated significantly with some of the latter measures, more so than the FFM scales. Impression management was measured with several scales. In the end of the testing session, participants were instructed explicitly to fake their answers. These active faking responses showed consistency across personality dimensions and also correlated strongly with impression management scores. Correcting the final pooled score (the four secondary factors combined) for impression management and faking produced fairly strong changes in the "short list" of participants ranking among the top 30, or 60. It is concluded that personality trait EI shows some promise while emotion identification tasks must probably be geared towards human emotion rather than abstract judgment of emotion as expressed in art or music.emotional intelligence; selection; impression management

Emotionally interactive agents

Models in language processing have researched how words are interpreted by humans. Many models presume the ability to correctly interpret the beliefs, motives and intentions underlying words. The interest relies also on how emotion motivates certain words or actions, inferences, and communicates information about mental state. As we will see below, some tutoring systems have explored this potential to inform user models. Likewise, dialogue systems, mixed-initiative planning systems, or systems that learn from observation could also benefit from such an approach. As these experimental data show, activating accessible constructs or attitudes through one set of stimuli can facilitate cognitive processing of other stimuli under certain circumstances, and can interfere with it under other circumstances. Some of the results support and converge on those centered on the constructs of current concern and emotional arousal. Future research has to take seriously into account this question: how to develop models where emotion interacts with cognitive processing. One example could be the work of Pitterman et al. (2010) where it is combined speech-based emotion recognition with adaptive human-computer modeling. With the robust recognition of emotions from speech signals as their goal, the authors analyze the effectiveness of using a plain emotion recognizer, a speech-emotion recognizer combining speech and emotion recognition, and multiple speech-emotion recognizers at the same time. The semi-stochastic dialogue model employed relates user emotion management to the corresponding dialogue interaction history and allows the device to adapt itself to the context, including altering the stylistic realization of its speech.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Beyond happiness: Building a science of discrete positive emotions.

While trait positive emotionality and state positive-valence affect have long been the subject of intense study, the importance of differentiating among several "discrete" positive emotions has only recently begun to receive serious attention. In this article, we synthesize existing literature on positive emotion differentiation, proposing that the positive emotions are best described as branches of a "family tree" emerging from a common ancestor mediating adaptive management of fitness-critical resources (e.g., food). Examples are presented of research indicating the importance of differentiating several positive emotion constructs. We then offer a new theoretical framework, built upon a foundation of phylogenetic, neuroscience, and behavioral evidence, that accounts for core features as well as mechanisms for differentiation. We propose several directions for future research suggested by this framework and develop implications for the application of positive emotion research to translational issues in clinical psychology and the science of behavior change. (PsycINFO Database Recor

ANALISIS PENERAPAN ARTIFICIAL INTELLIGENCE DALAM MENDETEKSI FRAUD PADA PROSES AUDIT (Studi Literatur Proses Audit di Asia dan Amerika)

This research aims to determine the influence of implementing Artificial Intelligence (AI) in detecting fraud in the audit process in Asia and America. This study uses a literature review method sourced from national and international journals originating from countries in Asia and America. The results obtained from this research indicate that Artificial Intelligence (AI) has a significant impact on the audit process, especially in detecting fraud. In terms of the sophistication priority scale possessed by AI, researchers can rank AI from the most advanced, namely Artificial Neural Network (ANN), Large Language Models (LLM), Complaint Management System (CMS), Behavior and Emotion Analytics Tool (BEAT), to Machine Learning, Big Data, Cloud Computing, and Fuzzy Methods, which are ranked last based on the most advanced AI

Differentiating normal and problem gambling: a grounded theory approach.

A previous study (Ricketts &amp; Macaskill, 2003) delineated a theory of problem gambling based on the experiences of treatment seeking male gamblers and allowed predictions to be made regarding the processes that differentiate between normal and problem gamblers. These predictions are the focus of the present study, which also utilised a grounded theory approach, but with a sample of male high frequency normal gamblers. The findings suggest that there are common aspects of gambling associated with arousal and a sense of achievement. The use of gambling to manage negative emotional states differentiated normal and problem gambling. Perceived self-efficacy , emotion management skills and perceived likelihood of winning money back were intervening variables differentiating problem and normal gamblers.</p