Aesthetic perception and judgement are not merely cognitive processes, but also involve feelings. Therefore, the empirical study of these experiences requires conceptualization and measurement of aesthetic emotions. Despite the long-standing interest in such emotions, we still lack an assessment tool to capture the broad range of emotions that occur in response to the perceived aesthetic appeal of stimuli. Elicitors of aesthetic emotions are not limited to the arts in the strict sense, but extend to design, built environments, and nature. In this article, we describe the development of a questionnaire that is applicable across many of these domains: the Aesthetic Emotions Scale (Aesthemos). Drawing on theoretical accounts of aesthetic emotions and an extensive review of extant measures of aesthetic emotions within specific domains such as music, literature, film, painting, advertisements, design, and architecture, we propose a framework for studying aesthetic emotions. The Aesthemos, which is based on this framework, contains 21 subscales with two items each, that are designed to assess the emotional signature of responses to stimuli’s perceived aesthetic appeal in a highly differentiated manner. These scales cover prototypical aesthetic emotions (e.g., the feeling of beauty, being moved, fascination, and awe), epistemic emotions (e.g., interest and insight), and emotions indicative of amusement (humor and joy). In addition, the Aesthemos subscales capture both the activating (energy and vitality) and the calming (relaxation) effects of aesthetic experiences, as well as negative emotions that may contribute to aesthetic displeasure (e.g., the feeling of ugliness, boredom, and confusion).

Previous research on unemployment and life satisfaction has focused on the effects of unemployment on individuals but neglected the effects on their partners. In the present study, we used dyadic multilevel models to analyze longitudinal data from 2,973 couples selected from a German representative panel study to examine the effects of unemployment on life satisfaction in couples over several years. We found that unemployment decreases life satisfaction in both members of the couple, but the effect is more pronounced for those who become unemployed (actors) than for the other couple members (partners). In both couple members, the reaction is attenuated if they share the same labor status after the job loss: Actors experienced a greater drop in life satisfaction if their partners were employed than if they were unemployed at the time of the job loss, and partners reacted negatively to the job loss only if they were employed or inactive in the workforce, but not if they were unemployed themselves. With respect to couple-level moderator variables, we found that both actors and partners reacted more negatively to unemployment if they had children. The reaction was also more negative in male actors than in female actors, but there was no difference between male and female partners. In sum, these findings indicate that changes in life satisfaction can be caused by major life events experienced by significant others.

Aesthetic evaluations are often couched in terms of emotional impact; for example, an artwork may be deemed fascinating, moving, or surprising. Such emotional responses have been called “aesthetic emotions.” Given the broad variety of terms used to conceptualize emotional reactions to art and to other elicitors of aesthetic responses, the authors performed an exploratory study aimed at mapping the conceptual domain of such terms by using a pile-sort task. Seventy-five items designating emotional reactions during aesthetic experiences were derived from the literature. Sixty students of the arts and related disciplines sorted the items into piles as determined by judged similarity. The authors used cluster and network analyses to draw up a highly granular conceptual map of the selected emotion terms. This map offers new information on the categorization and strength of associations between emotion terms that helps inform future conceptualizations and measures of specific aesthetic emotions. The analyses further revealed that complex and mixed emotional experiences of captivation, enchantment, and cognitive engagement are differentiated from emotions with purely negative or positive valence early on. The former emotions, which are regarded as typical of aesthetic experience, were found to lie at the heart of the conceptual domain of aesthetic emotion terms.

We propose to use a comprehensive path model of vocal emotion communication, encompassing encoding, transmission, and decoding processes, to empirically model data sets on emotion expression and recognition. The utility of the approach is demonstrated for two data sets from two different cultures and languages, based on corpora of vocal emotion enactment by professional actors and emotion inference by naïve listeners. Lens model equations, hierarchical regression, and multivariate path analysis are used to compare the relative contributions of objectively measured acoustic cues in the enacted expressions and subjective voice cues as perceived by listeners to the variance in emotion inference from vocal expressions for four emotion families (fear, anger, happiness, and sadness). While the results confirm the central role of arousal in vocal emotion communication, the utility of applying an extended path modeling framework is demonstrated by the identification of unique combinations of distal cues and proximal percepts carrying information about specific emotion families, independent of arousal. The statistical models generated show that more sophisticated acoustic parameters need to be developed to explain the distal underpinnings of subjective voice quality percepts that account for much of the variance in emotion inference, in particular voice instability and roughness. The general approach advocated here, as well as the specific results, open up new research strategies for work in psychology (specifically emotion and social perception research) and engineering and computer science (specifically research and development in the domain of affective computing, particularly on automatic emotion detection and synthetic emotion expression in avatars).

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