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A Meta-Analysis of 25 Years of Mood-Creativity Research: Hedonic Tone, Activation, or Regulatory Focus?

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Abstract

This meta-analysis synthesized 102 effect sizes reflecting the relation between specific moods and creativity. Effect sizes overall revealed that positive moods produce more creativity than mood-neutral controls (r= .15), but no significant differences between negative moods and mood-neutral controls (r= -.03) or between positive and negative moods (r= .04) were observed. Creativity is enhanced most by positive mood states that are activating and associated with an approach motivation and promotion focus (e.g., happiness), rather than those that are deactivating and associated with an avoidance motivation and prevention focus (e.g., relaxed). Negative, deactivating moods with an approach motivation and a promotion focus (e.g., sadness) were not associated with creativity, but negative, activating moods with an avoidance motivation and a prevention focus (fear, anxiety) were associated with lower creativity, especially when assessed as cognitive flexibility. With a few exceptions, these results generalized across experimental and correlational designs, populations (students vs. general adult population), and facet of creativity (e.g., fluency, flexibility, originality, eureka/insight). The authors discuss theoretical implications and highlight avenues for future research on specific moods, creativity, and their relationships.
A Meta-Analysis of 25 Years of Mood–Creativity Research:
Hedonic Tone, Activation, or Regulatory Focus?
Matthijs Baas, Carsten K. W. De Dreu, and Bernard A. Nijstad
University of Amsterdam
This meta-analysis synthesized 102 effect sizes reflecting the relation between specific moods and
creativity. Effect sizes overall revealed that positive moods produce more creativity than mood-neutral
controls (r.15), but no significant differences between negative moods and mood-neutral controls
(r⫽⫺.03) or between positive and negative moods (r.04) were observed. Creativity is enhanced most
by positive mood states that are activating and associated with an approach motivation and promotion
focus (e.g., happiness), rather than those that are deactivating and associated with an avoidance
motivation and prevention focus (e.g., relaxed). Negative, deactivating moods with an approach moti-
vation and a promotion focus (e.g., sadness) were not associated with creativity, but negative, activating
moods with an avoidance motivation and a prevention focus (fear, anxiety) were associated with lower
creativity, especially when assessed as cognitive flexibility. With a few exceptions, these results
generalized across experimental and correlational designs, populations (students vs. general adult
population), and facet of creativity (e.g., fluency, flexibility, originality, eureka/insight). The authors
discuss theoretical implications and highlight avenues for future research on specific moods, creativity,
and their relationships.
Keywords: mood, creativity, regulatory focus, hedonic tone, level of activation
Supplemental materials: http://dx.doi.org/10.1037/a0012815.supp
“The artist is a receptacle for emotions that come from all over the
place: from the sky, from the earth, from a scrap of paper, from a
passing shape, from a spider’s web.”
—Picasso, quoted in Christian Zervos, Conversation avec Picasso
[Conversation with Picasso]
“Feeling and longing are the motive forces behind all human endeavor
and human creations.”
—Albert Einstein, Religion and Science
To survive, people need to adapt to changing circumstances. To
prosper, people need to solve problems, generate new insights, and
create new products and services. Put differently, critical to both
survival and prosperity is creativity—the creation of something
new and unusual meant to improve one’s effective functioning
(Amabile, 1983; Eysenck, 1993; Runco, 2004; Simonton, 2003).
Accordingly, creativity has been studied in the psychological sci-
ences for decades, most notably since Guilford’s (1950) address to
the American Psychological Association, in which he pleaded for
the systematic study of creativity within psychology. Creativity
research now has its own place within most of the traditional
sub-areas in psychology, including social, organizational, person-
ality, cognitive, clinical, and child psychology.
Within these different sub-areas, mood stands out as one of the
most widely studied and least disputed predictors of creativity
(e.g., Isen & Baron, 1991; Mumford, 2003). The popularity of
mood as a predictor of creativity is partly due to the fact that mood
often serves as an intermediary state between a host of situational
and personality predictors, on the one hand, and creative perfor-
mance, on the other. Thus, once we understand how mood relates
to creativity, we may infer from the ways in which leadership
influences employee mood how leadership relates to employee
creativity (e.g., George & Zhou, 2002). Likewise, from the ways in
which group conflict influences individual moods, we may infer
how conflict relates to group creativity (e.g., Carnevale & Probst,
1998; De Dreu & Nijstad, in press). Additionally, from the way
preliminary task performance shapes emotion states, we may infer
how such task performance relates to creative performance on a
subsequent task (e.g., Madjar & Oldham, 2002).
In general, the mood– creativity literature breaks down into three
separate, yet interrelated, lines of inquiry. First, there is a large amount
of work comparing positive moods with affect-neutral control condi-
tions. In summarizing this line of work, Ashby, Isen, and Turken
(1999) concluded “It is now well recognized that positive affect leads
to greater cognitive flexibility and facilitates creative problem solving
across a broad range of settings” (p. 530). In a similar vein, Lyubomir-
sky, King, and Diener (2005) stated,
People in a positive mood are more likely to have richer associations
within existing knowledge structures, and thus are likely to be more
flexible and original. Those in a good mood will excel when the task
is complex and past learning can be used in a heuristic way to more
efficiently solve the task or when creativity and flexibility are re-
quired. (p. 840)
Matthijs Baas, Carsten K. W. De Dreu, and Bernard A. Nijstad, Department
of Psychology, University of Amsterdam, Amsterdam, the Netherlands.
Correspondence concerning this article should be addressed to Matthijs
Baas, Department of Psychology, University of Amsterdam, Roetersstraat
15, 1018 WB, Amsterdam, the Netherlands. E-mail: m.baas@uva.nl
Psychological Bulletin Copyright 2008 by the American Psychological Association
2008, Vol. 134, No. 6, 779– 806 0033-2909/08/$12.00 DOI: 10.1037/a0012815
779
This document is copyrighted by the American Psychological Association or one of its allied publishers.
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Thesis
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This thesis research art behaviors and their expression when artists work with ai image generators There are several different ways to look at art. In general, art is (or perhaps used to be) considered exclusively human. We expect it to encapsulate our emotions and express our experiences, which we deem human-specific (Chatterjee, 2014). Our ancestors were already engaging in artistic manifestations long before society as we know it existed. Where does art originate? Is it really exclusively human? Some approaches to the study of art argue that art is defined by the individual receiving it as such. This is the Reception theory. In this framework, the context the audience grants to a work made by AI determines the surrounding sentiments (Gombrich, 1995). One can also approach art as any work considered art by institutions. According to this theory, institutions (such as prestigious museums) control what we see as art (Dickie, 1974). both the institutional and the receptive point of view, art is defined as a kind of label that can be applied to any work. Unfortunately, audiences can be divided, and institutions can disagree. Cognitive science is now developing a more contemporary perspective on art by approaching art by the process. In other words, in cognitive theory, an object is art when it is made as such. With the current technological advancements of AI image generators, the most significant difference between AI-generated work and man-made work is the process. Therefore, the cognitive approach could be a good asset for separating AI and human creativity. This will be the focus of this thesis. Could cognitive theory shed new light on AI and create a distinction between human creativity and AI-generated images? What the art-making process entails exactly is a subject that still needs much research and has only recently gained more focus academically. For example, by considering art as a behaviour. This brings us to the main question: What are art behaviours from a cognitive science perspective, and are these behaviours present when producing works with generative image AI? To properly answer this, I interviewed artists to see what aspects of art behaviours they express when working with AI versus when working with their preferred traditional media. This way, the expression of art behaviour and their extent can be seen by comparing the two interviews. This could provide new insights into what differentiates human-made works from AI-generated images. In order to do this, I will first answer the following sub-questions: 1. What are art behaviours? 2. Can AI-generated images be seen as art from a cognitive science approach? 3. What type of art behaviours are present in the experience of an artist when generating images? Chapter 1 explains what art behaviours are exactly, where they originate, and discusses the Artification theory. I propose the following aspects that are inherent to art behaviour: - a feeling of expressing a part of yourself or your experiences through imagination - a lack of functional goals or purpose. - a feeling of emotional involvement - a conflicting process where the end product differs from the original aim - possibly, a feeling of originality and value I will ask the interviewees about these aspects to see if they express art behaviour when working with AI. In Chapter 2, I will discuss how (generative image) AI works and how different studies of art perceive AI. Do they consider generated AI images creative? Here, I explain that AI images are not perceived equally to human works, and that the cognitive approach quickly dismisses AI as ‘never creative’ because it lacks the process. However, artists might experience art behaviours when working with generative AI. If there is a clear difference between showing art behaviour when working with AI works and with traditional works, this could explain the anthropocentric bias surrounding AI works. Chapter 3 will present the research's methodology/operationalisation and bring together chapters 1 and 2. I will try to answer the question: What type of art behaviours are present in an artist's experience when generating images? For this, I interviewed three participants twice: once while working with AI (Dall-E2) and once while working with traditional media. I conclude that most aspects of art behaviours discussed tend to be more present when working with the preferred medium than when working with AI. If anything, AI shows us that the study of art is far from dichotomous and still has anthropo-centrically biased tendencies. 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