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Richards proposed that everyday creativity—creative actions that are common among ordinary people in daily life, such as drawing, making recipes, writing, and any activity done with the purpose of being creative—both fosters and reflects psychological health. To explore when people are more likely to do something creative during the day, and to see who tends to act more creatively, we conducted a week-long experience-sampling study with a sample of young adults. Throughout the day, people’s actions and feelings were randomly sampled, with an emphasis on whether people were doing something creative. Consistent with the notion of everyday creativity as a psychological strength, within-person models showed that people who reported feeling happy and active were more likely to be doing something creative at the time. Between-person models found that openness to experience and conscientiousness had large effects on whether people spent their time on creative pursuits. Neither negative states (e.g., momentary feelings of anger, stress, and self-consciousness) nor traits (e.g., neuroticism) significantly predicted creative activity. The findings support Richards’s theorizing about everyday creative behavior as a cause and effect of positive psychological processes, and they illustrate the value of experience sampling for uncovering what creativity looks like in people’s idiosyncratic environments.
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Psychology of Aesthetics, Creativity, and the
Everyday Creativity in Daily Life: An Experience-Sampling
Study of “Little c” Creativity
Paul J. Silvia, Roger E. Beaty, Emily C. Nusbaum, Kari M. Eddington, Holly Levin-Aspenson,
and Thomas R. Kwapil
Online First Publication, February 10, 2014.
Silvia, P. J., Beaty, R. E., Nusbaum, E. C., Eddington, K. M., Levin-Aspenson, H., & Kwapil, T.
R. (2014, February 10). Everyday Creativity in Daily Life: An Experience-Sampling Study of
“Little c” Creativity. Psychology of Aesthetics, Creativity, and the Arts. Advance online
Everyday Creativity in Daily Life: An Experience-Sampling
Study of “Little c” Creativity
Paul J. Silvia, Roger E. Beaty, Emily C. Nusbaum, Kari M. Eddington, Holly Levin-Aspenson,
and Thomas R. Kwapil
University of North Carolina at Greensboro
Richards proposed that everyday creativity— creative actions that are common among ordinary people in
daily life, such as drawing, making recipes, writing, and any activity done with the purpose of being
creative— both fosters and reflects psychological health. To explore when people are more likely to do
something creative during the day, and to see who tends to act more creatively, we conducted a
week-long experience-sampling study with a sample of young adults. Throughout the day, people’s
actions and feelings were randomly sampled, with an emphasis on whether people were doing something
creative. Consistent with the notion of everyday creativity as a psychological strength, within-person
models showed that people who reported feeling happy and active were more likely to be doing
something creative at the time. Between-person models found that openness to experience and consci-
entiousness had large effects on whether people spent their time on creative pursuits. Neither negative
states (e.g., momentary feelings of anger, stress, and self-consciousness) nor traits (e.g., neuroticism)
significantly predicted creative activity. The findings support Richards’s theorizing about everyday
creative behavior as a cause and effect of positive psychological processes, and they illustrate the value
of experience sampling for uncovering what creativity looks like in people’s idiosyncratic environments.
Keywords: everyday creativity, little-c creativity, experience sampling, openness to experience, ecolog-
ical momentary assessment
Creativity research knows a lot about genius and eminence,
about the “Big C” creative greats (e.g., Simonton, 1999), but much
less about everyday “little c” creativity, the common hobbies and
passions of ordinary people who want to do something creative.
Whether it’s making greeting cards, rocking out in a basement,
deploying an arsenal of scalloped scrapbooking scissors, whiling
away a psychology lecture by knitting, weaving a necktie out of
duct tape, or writing maudlin poetry best kept to oneself, people
spend a lot of time doing creative things simply because of
personal enjoyment and fulfillment. The resulting products might
not be particularly innovative, desirable, or effective, but as Rich-
ards (2007) points out, the sheer mass of ordinary creative activity
says something important about human nature.
In her writings, Richards (2007, 2010) has called attention to
everyday creativity and its role in psychological development.
Although her theorizing isn’t easily condensed, one theme is that
everyday creativity is both a cause and a consequence of positive
development. Engaging in creative pursuits allows people to ex-
plore their identities, form new relationships, cultivate compe-
tence, and reflect critically on the world. In turn, the new knowl-
edge, self-insight, and relationships serve as sources of strength
and resilience. Not much is known, however, about what everyday
creativity looks like empirically. Most research has used cross-
sectional interviews about past creative actions (e.g., Richards,
Kinney, Benet, & Merzel, 1988) and self-report scales that ask
how often people have done different kinds of common creative
pursuits (e.g., Batey, 2007; Hocevar, 1979).
To understand everyday creativity, researchers should examine
what it looks like in people’s natural environments as it happens.
Experience sampling methods—a family of methods that inten-
sively assess people as they go about their normal lives (Conner,
Tennen, Fleeson, & Barrett, 2009; Hektner, Schmidt, & Csikszent-
mihalyi, 2007)— offer compelling tools for problems like every-
day creativity. In the present research, we conducted an experience
sampling study of everyday creativity in the daily lives of a sample
of young adults. Our primary purpose, as in much experience
sampling, was largely exploratory and descriptive: intensively
measuring what people are doing in their everyday, self-selected
environments provides a nuanced and ecological perspective on a
phenomenon (Bolger & Laurenceau, 2013). In the case of every-
day creativity, experience sampling can illuminate some important
questions: How often do people do something creative? What
kinds of emotions and feelings typify everyday creative activity?
What kinds of people tend to spend their time on creative pursuits?
Paul J. Silvia, Roger E. Beaty, Emily C. Nusbaum, Kari M. Eddington,
Holly Levin-Aspenson, and Thomas R. Kwapil, Department of Psychol-
ogy, University of North Carolina at Greensboro.
Correspondence concerning this article should be addressed to any of the
first three authors at Department of Psychology, P. O. Box 26170, Uni-
versity of North Carolina at Greensboro, Greensboro, NC 27402-6170.
Email:,, or
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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Psychology of Aesthetics, Creativity, and the Arts © 2014 American Psychological Association
2014, Vol. 8, No. 1, 000 1931-3896/14/$12.00 DOI: 10.1037/a0035722
Guided by Richards’s writings, however, our hypotheses weren’t
entirely exploratory. Given the role of creative activity in positive
development, one would expect creative activity throughout the
week to be associated with markers of positive experience, such as
positive traits (e.g., openness to new experiences) and positive
states (e.g., feelings of happiness and positive activation).
A total of 79 students at UNCG— 61 women, 18 men—partic-
ipated in the week-long study. Some students received credit
toward a voluntary research participation option in one of their
classes; others received up to $20 in cash. To expand the variabil-
ity in personality and creative pursuits, we made a special effort to
recruit students (n26) with majors in the arts (Silvia & Nus-
baum, 2012).
The first phase of the study took part in the lab. After complet-
ing a consent form, participants learned how to use the phone-
based survey system and then completed a series of self-report
questionnaires. After the lab session, they received surveys via
their cell phone for the rest of the day and for the following seven
Between-person questionnaires. We assessed personality us-
ing the NEO FFI 3 (McCrae & Costa, 2010), a 60-item scale that
measures the five major factors of personality: neuroticism, extra-
version, openness to experience, agreeableness, and conscientious-
ness. All five factors influence creativity in some regard, but the
most central by far is openness to experience, which strongly
predicts creativity across its many levels (e.g., McCrae, 1987;
Silvia, Nusbaum, Berg, Martin, & O’Connor, 2009). We naturally
expected openness to predict how often people engaged in creative
activities in everyday life.
In addition to personality, we measured people’s self-reports of
how often they engage in everyday creativity. The Biographical
Inventory of Creative Behaviors (BICB; Batey, 2007) presents 34
common kinds of everyday creative behaviors (e.g., writing a
poem, drawing a picture, making a recipe) and asks people if they
have done them within the past year. People respond on a 0/1
(no/yes) scale. Unlike scales such as the Creative Achievement
Questionnaire (CAQ; Carson, Peterson, & Higgins, 2005), the
BICB emphasizes common ways that people express little-c cre-
ativity across a wide range of domains. Past research has found
good evidence for the BICB scores’ reliability and validity (Silvia,
Wigert, Reiter-Palmon, & Kaufman, 2012).
Experience sampling design. We delivered the surveys using
the participants’ own cell phones. People provided their cell phone
numbers along with the 12-hr time period that they preferred to
receive the surveys. For example, people could choose to get
survey calls between 8 a.m. to 8 p.m., 10 a.m. to 10 p.m., 1 p.m.
to 1 a.m., or any other convenient 12-hr window. Because some
college students keep eccentric hours, allowing personalized sur-
vey windows ensured that the surveys arrived during the waking
hours, thus reducing missing data (Silvia, Kwapil, Eddington, &
Brown, 2013). An interactive voice response (IVR) system, run-
ning Telesage’s SmartQ (Telesage, 2009), administered the auto-
mated surveys. The software generated eight survey calls per day,
at quasi-random times, within each person’s 12-hr window. If
people missed a call, they could call into the system within 5
minutes to complete it, which further reduces missing data
(Burgin, Silvia, Eddington, & Kwapil, 2013). Participants re-
sponded to survey items using the phone keypad. They were told
to respond to the items based on their momentary feelings,
thoughts, and actions at the time of the call.
Survey items. Table 1 lists the items people completed at each
call. Our central question concerned everyday creativity: People
responded to “Are you doing something creative?” using a binary
no/yes scale. This question was deliberately general so it could
include the wide range of activities that could be done creatively.
To assess the emotional and motivational qualities of situations
involving creative work, we included a cluster of items that as-
sessed a range of inner states. Several items assessed common
emotions people experience in everyday life, such as feeling
happy,sad,anxious, and angry. Other items asked about other
experiences, such as whether people felt active,restless,annoyed,
discouraged, and self-conscious. People responded to these items
using a 7 point scale (1 not at all,7very much). The items
assessing inner states were presented in a different random order at
each call, which should wash out order effects, minimize reactiv-
ity, and reduce the mindless “click through” that can happen when
participants become accustomed to items that have been presented
dozens of times. Finally, to gain information on the social context,
we asked if people were alone or with other people. Most of these
items have been used in our past experience sampling work, which
over the years has developed items that reflect the range of
common feelings that college students report in a typical week
(e.g., Brown, Silvia, Myin-Germeys, & Kwapil, 2007; Kwapil,
Brown, Silvia, Myin-Germeys, & Barrantes-Vidal, 2012).
Analytic Approach and Descriptive Statistics
For the analyses, we excluded three participants who had un-
usually poor experience-sampling response rates (i.e., five or fewer
surveys). People received different numbers of calls—the initial
sessions started at different times of the day, and technical glitches
Table 1
Items in the Experience Sampling Survey
Item Response scale
Are you doing something creative? 0 (no),1(yes)
Before the call, I felt. . .
Happy 1 (not at all)to7(very much)
Active 1 (not at all)to7(very much)
Sad 1 (not at all)to7(very much)
Discouraged 1 (not at all)to7(very much)
Restless 1 (not at all)to7(very much)
Anxious 1 (not at all)to7(very much)
Angry 1 (not at all)to7(very much)
Annoyed 1 (not at all)to7(very much)
Self-conscious 1 (not at all)to7(very much)
Are you alone or with other people? 0 (alone),1(with others)
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and problems shortened or extended the data collection period for
some participants— but they completed an average of 38.12 sur-
veys (Mdn 39, range 6 to 62). The overall response rate was
roughly 65%, which is comparable, and somewhat higher, than our
past research with cell phones (Burgin et al., 2013) and typical for
experience sampling research. We also excluded surveys that took
less than 90 seconds, which typically reflects “clicking through” or
hanging up midsurvey. Overall, each survey took on average 2.65
minutes (Mdn 2.60, range 1.51 to 6.3 minutes).
Experience sampling studies have two data levels: a within-
person level (the items asked dozens of times throughout the week,
such as people’s momentary emotions) nested in a between-person
level (the questions asked once during the initial lab session, such
as personality). Analyzing such data thus typically involves mul-
tilevel models, which can accommodate the nested structure of the
data (Heck & Thomas, 2009; Silvia, 2007). We conducted the
multilevel models using Mplus 7.11. Within-person predictors
were centered at each person’s own mean; between-person predic-
tors were centered at the sample’s grand mean.
Missing data in experience sampling is largely “beep wise”: the
data for between-person constructs are generally 100% complete,
but people will have varying numbers of missed beeps (Silvia et
al., 2013). One virtue of multilevel models is their ability to handle
unequal numbers of within-person units and to estimate parameters
efficiently despite widespread missingness (Heck & Thomas,
2009). Simulation research shows that full-information maximum
likelihood, the method used here, can effectively recover popula-
tion estimates despite extensive missingness (Enders, 2010). This
is true even for multilevel designs when missingness is extensive
(most observations are missing) and variable (people differ widely
in how much data are missing), according to recent simulations
(Silvia, Kwapil, Walsh, & Myin-Germeys, in press). We’re thus
confident that the analyses are robust to the missing data in the
present sample.
Within-Person Predictors of Doing Something Creative
The final dataset had the richness typical of experience-
sampling designs: the analyses were based on nearly 2,300 surveys
of what people were doing and feeling in their everyday environ-
ment. We found that creative action was quite common: people
said they were doing something creative 22% of the time that they
were called.
When were people more likely to report doing something cre-
ative? What other aspects of everyday life predicted creative
behavior? Our first multilevel model explored the effects of mo-
mentary emotional and motivational states. For this model, all 9
states listed in Table 1 were entered simultaneously as within-
person predictors, and creative activity was the binary outcome.
Table 2 displays the results. Only two states emerged as significant
predictors—feeling happy and feeling active, the two states that
have most consistently fostered creativity in the experimental
literature (Baas, De Dreu & Nijstad, 2008). Notably, negative and
aversive states, from passive states like sadness to activated states
like anger and anxiety, had no effects on the likelihood of creative
activity. An additional model explored whether doing something
creative was more likely when people were alone or with others;
no significant difference appeared (see Table 2).
Finally, experience sampling allows us to understand variability
in within-person relationships. For the sample as a whole, for
example, the slope relating happiness to creativity was significant,
but this sample slope is (roughly) the average of each individual
participant’s slope. We explored if people varied significantly in
their within-person slopes by reestimating the model with random
effects (using Monte Carlo integration) and examining the vari-
ance components for the slopes, which represent the between-
person heterogeneity in the slopes. For example, if the happiness–
creativity slope was positive for most of the sample but negative
for some of it, the variance component for the slope would be large
and significantly different from zero. None of the variance com-
ponents were significant (e.g., for happy, p.902, and for active,
p.221), so the sample didn’t have significant variability in the
within-person slopes.
Between-Person Predictors of Doing Something
What kind of person was most likely to be doing something
creative? Our next models explored between-person predictors of
everyday creative behavior. We first examined the role of the Big
Five factors as simultaneous predictors of the binary creativity
outcome. Table 3 displays the results. Not surprisingly, openness
to experience had the largest effect: as openness increased, people
were much more likely to be doing something creative. Figure 1
shows the predicted probability of doing something creative as a
function of openness. The X-axis shows the raw scores for open-
ness, which are centered at the sample mean of zero. The figure
shows the estimated probabilities for raw values ranging
from 1.5 to 1.5, which reflect a range of 3 standard deviations
(SD) above and below the mean of 0. People who were at 3 SD
below the mean in openness had only a 12% likelihood of doing
something creative; people 3 SD above the mean in openness, by
contrast, had a 40% chance of doing something creative.
The only other significant effect, curiously enough, was for
conscientiousness (see Table 3). As conscientiousness increased,
people were more likely to be doing something creative. The small
literature on conscientiousness and creativity is complex and in-
consistent (see Reiter-Palmon, Illies, & Kobe-Cross, 2009), but we
suspect this effect appeared in our sample because of the high
Table 2
Within-Person Predictors of Doing Something Creative at
the Moment
Predictor bp95% CI
Happy .077 .018 .013, .141
Active .081 .047 .001, .161
Sad .001 .983 .109, .133
Discouraged .021 .756 .132, .112
Restless .068 .145 .145, .023
Anxious .046 .346 .034, .142
Angry .023 .663 .112, .082
Annoyed .005 .915 .090, .095
Self-conscious .006 .882 .060, .085
With others .090 .590 .237, .417
Note. The coefficients are unstandardized logistic coefficients. The pre-
dictor “With others” was estimated in a separate model.
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proportion of music majors, a conscientious group that spends
much of the day devoted to their craft. In fact, the arts majors were
significantly higher in both openness (standardized ␤⫽.38, p
.001) and conscientiousness (standardized ␤⫽.32, p.004) in
our sample.
We then explored the BICB scale as a predictor. When esti-
mated by itself, the BICB strongly predicted the likelihood that
people were doing something creative (see Table 3). Because
BICB scores correlate with openness to experience (r.34 in this
sample), we ran an additional model that included the Big Five
factors and the BICB as predictors. The BICB remained a strong
predictor despite controlling for personality (see Table 3), a find-
ing that offers unique support for the scale as a measure of
everyday creativity.
Finally, we explored differences between students with and
without majors in the arts. Around a third of the sample had a
major in the arts (primarily music), and it’s possible that this group
was biasing the high overall probability (22%) of doing something
creative. We estimated a model in which people’s major (scored 0
for nonarts major and 1 for arts major) predicted doing something
creative. As one would expect, people’s major had a large effect
(see Table 3). This effect can be unpacked by considering the
estimated probabilities of doing something creative for the two
groups. People with arts majors were doing something creative
39% of the time; people without arts majors were doing something
creative 19% of the time. It’s notable, then, that people without
majors that required ongoing daily involvement in creative pur-
suits nevertheless were doing something creative nearly 20% of
the time during a typical week.
What does everyday creativity look like in everyday life? Ex-
perience sampling methods are ideal for observing the diversity of
what people are doing and thinking in their natural environments.
In the present research, we explored everyday creativity in the
daily lives of a sample of young adults. First, we found that the
Table 3
Personality Predictors of Doing Something Creative at
the Moment
Model Predictor bp 95% CI
1. Personality Neuroticism .023 .930 .482, .527
Extraversion .354 .216 .206, .914
Openness to experience .672 .035 .046, 1.298
Agreeableness .464 .178 1.140, .211
Conscientiousness .611 .032 .053, 1.170
2. BICB BICB (Alone) 4.048 .001 2.277, 5.819
BICB 3.467 .001 1.561, 5.373
3. Arts majors Arts major 1.203 .001 .639, 1.676
Note. The coefficients are unstandardized logistic coefficients. BICB
Biographical Inventory of Creative Behaviors. BICB (Alone) is the effect
when BICB is estimated as the only predictor.
Figure 1. The probability of doing something creative in daily life as a function of openness to experience.
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frequency of doing something creative was quite high, around
22%, in light of all the things that people could do and must do
during a day. Second, we explored the daily context of creative
activity, with an emphasis on inner experiences associated with
doing something creative. When people reported doing something
creative, they reported feeling significantly happier and more
active. It’s notable that these findings, taken from people’s uncon-
trolled and idiosyncratic environments, align with the large exper-
imental literature on affect and creativity. The large mood-and-
creativity literature isn’t easily captured in a snapshot, but Baas
et al.’s (2008) meta-analysis found that active and positive states,
such as happiness, had the largest effects on creativity. The non-
significant variance components indicated that people didn’t vary
appreciably in their within-person slopes linking feelings to cre-
ativity, which is an intriguing result in its own right.
And third, we explored which traits predicted spending time on
creative pursuits. Openness to experience, a trait associated with
curiosity, imagination, and behavioral flexibility, strongly pre-
dicted spending time on something creative; conscientiousness
significantly predicted everyday creativity, too. Our measure of
openness to experience yields only a global domain score, and it
would be interesting in future work to break openness’s effect
down based on its facets. In the Openness/Intellect model
(DeYoung, Quilty, & Peterson, 2007), one would expect much
larger effects for openness than for intellect (Nusbaum & Silvia,
2011). In the Five Factor Model (McCrae & Costa, 2008), one
would probably find larger effects for the facets associated with
imagination and aesthetic interests. And in the HEXACO (Ashton
& Lee, 2007), one would expect larger effects for the creativity
and aesthetic appreciation facets relative to the unconventionality
and inquisitiveness facets. Beyond personality, having a major
related to the arts and having high BICB scores, not surprisingly,
predicted spending more time doing something creative.
The null effects strike us as equally telling. It might seem
surprising that nothing appeared for the many negative emotions
that we measured, given the long interest in creativity and psy-
chopathology as well as cultural stereotypes about creativity being
motivated by despair and anguish. But the pattern of findings—
people doing something creative are more likely to feel happy and
enlivened—fits nicely with Richards’s (2007, 2010) model of
everyday creativity, which views it as a psychologically healthy
state that fosters personal growth, and it resembles the phenome-
nology of flow, a state long connected to creativity (Csikszentmi-
halyi, 1990). Likewise, the traits that predicted creativity reflect
both imagination (high openness) and self-regulation (high con-
scientiousness). The stereotype of a neurotic, impulsive, dysregu-
lated person seeking solace in creativity was clearly not supported
in this study (Beaty, Silvia, Nusbaum, & Vartanian, 2013; Silvia &
Kaufman, 2010).
Limitations and Future Directions
In the present work, we measured creative activity with a simple
binary item, based on the everyday-creativity view that any activ-
ity can be done in novel ways with creative intentions. This
measurement choice has its virtues—it forces people to commit to
an answer rather than hedge, and it affords estimates of the overall
base rate of doing something creative— but it has some clear
limitations as well. For one, the binary quantitative outcome ob-
scures the specific activities that people were pursuing. People
indicated whether they were doing something creative, but what
exactly they were doing— be it rehearsing with their jazz trio or
knitting the dog a bib—went unmeasured. In experience sampling,
there’s a tradeoff between how often people can be surveyed each
day and how much information one can collect at each survey
(Silvia et al., in press). The highly intensive within-day method we
used works best with small sets of short quantitative items, so we
don’t have qualitative information on the nuances of the activity
and context.
A natural next step would be to employ alternative designs that
could provide more detail and texture about the activities people
pursue and how different activities relate to personality and inner
experience. One possibility would be to use an end-of-day diary
design that asked about experiences and activities during the day,
using both rating scales and qualitative free responses, every
evening for several weeks. Another would be to use an event-
contingent method (Moskowitz & Sadikaj, 2012), in which people
complete a detailed diary and survey whenever a predefined
event—such as doing something creative— happens. These alter-
nate designs cover the other side of the trade-off: they don’t
capture as many random points in a person’s typical day, but they
provide more detail about certain parts of it. In either case, expe-
rience sampling is a fertile method for creativity research, one that
we hope gets more attention in future work.
Our snapshot of everyday creativity provides strong support for
Richards’s perspective on everyday creativity, which emphasizes
the important psychological strengths concealed by common cre-
ative action. The creative products might seem frivolous, amateur-
ish, or weird, but the creative process that yielded them appears
important to positive psychological development. More generally,
this research highlights the value of experience sampling for
research on aesthetics, creativity, and the arts. With some excep-
tions (e.g., Bailes, 2006; Beaty et al., 2013; Nusbaum et al., in
press; Tschacher et al., 2012), the field has not often taken its tools
outside of the sterile lab and into the idiosyncratic and uncon-
trolled environments in which people experience and create art.
Not every question lends itself well to experience sampling, but the
method is a fruitful way of knowing what creativity and the arts
look like in the mystifying “real world.”
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Received August 2, 2013
Revision received October 15, 2013
Accepted October 21, 2013
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... Participating in creative activities is often associated with positive emotions and enhanced feelings of wellbeing (Acar, Tadik, Myers, Sman, & Uysal, 2020;Fancourt & Finn, 2019;Papagiannaki & Shinebourne, 2016;Silvia et al., 2014). However, relative to the general population, creative professionals do not necessarily show superior well-being, despite having high levels of active creative engagement (Akinola & Mendes, 2008;Fujiwara, Lawton, & Dolan, 2015;Kyaga, 2014). ...
... Studies of everyday creativity also have found conflicting relationships between negative affect and creativity. For example, some studies find negative affect to be a significant antagonist of creativity (Conner et al., 2018;Conner & Silvia, 2015;Karwowski et al., 2021), while others find non-significant relationships between negative affect and creativity (Karwowski et al., 2017, Study 1;Silvia et al., 2014), or that particular negative emotions like fear may have a weak negative relationship with creativity, while anger may have a small positive relationship with creativity (Karwowski et al., 2017, Study 2). ...
... This link is also corroborated in daily life studies: those higher in openness report a higher quantity and intensity of daily creativity (Carson, Peterson, & Higgins, 2005;Conner & Silvia, 2015). For example, one study found that those higher in openness had a 40% probability of doing something creative compared to a 12% probability for people lower in openness Silvia et al., 2014). Openness is also found to moderate the relationship between emotions and creativity; a weekly diary study of creativity within the workplace found that openness interacted with high-activated positive moods leading to greater innovative work behavior (Madrid, Patterson, Birdi, Leiva, & Kausel, 2014). ...
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Participating in creative activities is associated with increased positive emotions and enhanced subjective well-being in general populations. However, these relationships are less understood in the daily lives of creative individuals who regularly engage in both professional creative behaviors and everyday creative experiences. Therefore, in this study, we recruited a sample of creative adults (N= 290; creative professionals, students studying creative disciplines, and hobbyists engaged in 20+ hours of creative activities per week) who provided daily responses on their creative behaviors, emotions, and flourishing over two weeks. Creative adults were found to be the most creative on days with highly activated positive emotions and increased well-being and were significantly less creative on days with negative emotions. Individuals with higher levels of openness have stronger ties between their emotions and overall daily creativity and everyday creativity than those with lower levels of openness. Increased openness does not appear to have the same moderating effects on professional creativity and emotion relationships. Finally, high conscientiousness and low neuroticism were also found to predict increased levels of creative activity. Overall, these findings provide novel insights into the links between the specific nature of daily creative activities and the personality and subjective well-being of creative individuals.
... Capturing data as we live our lives outside a rather artificial laboratory may increase the meaningfulness and ecological validity of observed within and between-person variance (for a critical discussion see, Ram et al., 2017). Due to these positive assets, EMA has also been successfully applied in creativity research (Benedek et al., 2017;Conner & Silvia, 2015;Karwowski et al., 2017;Silvia, Beaty, Nusbaum, Eddington, Levin-Aspenson, & Kwapil, 2014). Recently, Cotter and Silvia (2019) provided a helpful overview and short guideline to study creativity by the use of EMA (Czerwonka, 2019). ...
... However, to date, EMA studies have assessed creativity mostly by self-ratings, such as "Are you doing something creative [at this moment]?" (e.g., Silvia, Beaty, Nusbaum, Eddington, Levin-Aspenson, & Kwapil, 2014; see also Cotter & Silvia, 2019). Although this approach is worthwhile and interesting, creative ideation performance as a measure of creative potential (Runco & Acar, 2012) and the moment-to-moment fluctuation of creative abilities have not been investigated with EMA protocols so far. ...
... In their meta-analysis, Baas et al. (2008) reported a significant relationship between positive affect and creativity of low to medium size. Accordingly, several EMA and daily diary studies indicated an association between self-rated creative activities and the moment-to-moment fluctuations of positive (activated) affect in everyday life (Benedek et al., 2017;Karwowski et al., 2017;Silvia, Beaty, Nusbaum, Eddington, Levin-Aspenson, & Kwapil, 2014;To et al., 2012). In a daily diary study, which took place for thirteen days in a large sample of 658 participants, Conner and Silvia (2015) found that people were more creative on days when they reported more positive affect. ...
Creative ideas in daily life show substantial variation in quality. Yet, most studies investigate the creative ideation process in highly controlled laboratory contexts, which challenges the ecological validity of creativity research findings. In this article, we advocate the use of ambulatory assessments of creative ideation to gain deeper insight into the variability of ideation processes (between- and within-subjects) in everyday life. We demonstrate this approach by the example of the ambulatory battery of creativity (ABC), which constitutes a reliable and valid approach to assess divergent thinking ability in the verbal and figural domain in everyday life context. Furthermore, it differentiates between-person and within-person variation of creative ideation performance. The first part of this paper will shortly describe the general approach using ABC as an example. In the second part, we use the 7 C’s heuristic to explore applications and implications of this novel method for creativity research. We focus on four C’s with special relevance for ambulatory assessment: Creator, Creating, Context, and Curricula. To this end, we review the findings of strongly controlled laboratory studies and discuss and illustrate applications of the ambulatory assessment. We conclude that the assessment of creative ideation performance in the field might help move the spotlight of creative ideation research from the laboratory to more naturalistic settings. This would increase the ecological validity of creative ideation research and facilitate fresh or unprecedented perspectives on past and future questions on a person’s creative potential and its moment-to-moment fluctuation.
... Creative activities include creative acts and products of people in their daily lives. These activities describedepending on the measure -minor or major accomplishments in different areas of daily life (Silvia et al., 2014;Weiss et al., 2021a). These are skill-related typical behaviors, which are situated in the everyday life of a person. ...
... the domains from which a wider range of items were selected, being more accessible to a little-c population in terms of capturing passions of creative people within the general population (Silvia et al., 2014). ...
Creativity can be measured with a variety of methods including self-reports, others reports, and ability tests. While typical self-reports are best understood as weak proxies of creativity, biographical reports that assess previous creative activities seem more promising. Drawbacks of such measures – including skewed item distributions, a lack of measurement invariance across sex, and low convergent validity with established measures of creativity (such as divergent thinking tasks) – might be attributable to issues of item sampling. Therefore, we use a meta-heuristic algorithm (Ant Colony Optimization) to develop a short-scale of creative activities that a) maintains coverage of the original domains, b) provides good model fit, c) has good reliability, d) demonstrates balanced item difficulty, e) is measurement invariant across sex, and f) possesses convergent validity with divergent thinking. For an 8-item short version of the original Inventory of Creative Activities and Achievements, we identified an item set that satisfies the most pre-specified criteria using data from N = 296 adults. In a replication sample (N = 327) we replicate the findings and report good model fit, good reliability, adequate item difficulty, and measurement invariance across sex. We derive recommendations on the measurement of creative activities, and discuss implications for understanding creativity in general.
... This is relevant because in studies only using subjective (self-report) measures there might be potential common method bias (Podsakoff & Organ, 1986). Also, our daily diary approach focusing on a within-person level expands the prior literature on creativity which primarily used cross-sectional and longitudinal design (Lewis & Lovatt, 2013;Silvia et al., 2014). ...
... This implies that on the specific days when employees design their work playfully, they may also experience more flow and creativity. Although previous studies provide insights into individual differences in flow (or affect) and creativity (Madrid & Patterson, 2018;Schutte & Malouff, 2020), as well as withinperson relationships (Silvia et al., 2014), they rarely addressed questions regarding the proactive behaviours that individuals may use to improve creativity. The current study using a withinperson level research design responds to the research question what specific behaviour employees may use to enhance their own creativity on a daily basis. ...
Playful work design refers to the process through which employees proactively create conditions within work activities that foster enjoyment and challenge without changing the design of the job itself. Using flow theory, we propose that employees experience more work-related flow (work enjoyment, work absorption, and intrinsic work motivation) on the days when they playfully design their work – with positive implications for creative performance on these days. In addition, based on trait activation theory, we hypothesize that flow proneness strengthens the relationship of playful work design with work-related flow. A daily diary approach was employed to test the hypotheses. In total, 149 participants completed both baseline and daily questionnaires across five consecutive working days (total N = 552). Alternative Uses Task was used to measure objective creativity at work. Multilevel analysis showed that playful work design was positively associated with work-related flow, and work-related flow was significantly related to creativity – on a daily basis. In addition, employees high (vs. low) in flow proneness reported more flow and creativity when playfully designing their work. We discuss the theoretical and practical implications of these findings.
... Then, the survey asked a series of questions about thought content; the stem "My thoughts were…" preceded a series of 11 descriptions of the content and quality of one's current thoughts (e.g., dreamlike, novel, interesting; 1 = not at all to 7 = very much). One survey item in this section asked whether one's "thoughts were related to a creative project", and this variable is how we operationalized creative project thought (note that everyday creativity is commonly measured with a single survey item; Connor & Silvia, 2015;Han et al., 2019;Silvia et al., 2014). The next part of the ESM survey inquired about behavioral activities; the stem "I was doing something…" preceded five descriptions of one's current activities (e.g., creative, enjoyable, challenging; 1 = not at all to 7 = very much). ...
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Creativity has long been conceptually linked to experiences of emotion and mind wandering, yet these empirical relationships remain unclear, and few studies have explored the thoughts and emotions of creative people in daily life. To investigate how creativity relates to everyday cognitive and affective experiences, the present study (N = 159) used experience sampling to examine how creative cognition (divergent thinking ability) and creative behavior (self-reported creative activity and achievement) measured in the lab may predict thought content, affective state, and the frequency of mind wandering (i.e., task-unrelated thought) in daily life. Additionally, we assessed in-the-moment thoughts and emotions predictive of thinking about a creative project in everyday life (i.e., “creative project thought”). We found that each form of creativity was generally associated with positively-valenced experiences, such as having pleasant thoughts, enjoying one’s everyday activities, and feeling motivated and inspired. We also found that positive, activating emotions (happy and energetic) were positively associated with divergent thinking ability and in-the-moment creative project thought. Furthermore, positive, deactivating emotions (relaxed and connected) negatively predicted momentary creative project thought—indicating that positive affect can be tied to less creative thinking, depending on the activation level of emotions. No relationship was found between daily-life mind wandering frequency and divergent thinking ability or creative behavior/achievement, suggesting that the overall amount of task-unrelated thought in everyday life is not related to individual creativity. Taken together, the present findings provide novel evidence on the everyday experiential correlates of creative thinking and behavior.
... There is the assertion that a creative mind is a healthy mind and vice versa (Richard, 2010;Conner and Silvia, 2015;Benedek et al., 2019). When creativity is in action, the individual feels happy and thereafter even happier after the creative process; people feel happier and therefore actively involved and relaxed (Silvia et al., 2014;Conner et al., 2017). Sternberg (2012) has argued that creativity can predict college success above and beyond just what students obtain from school examination scores. ...
Full-text available
The purpose of this article was to analyze chemistry teachers’ interest, literacy, self-efficacy, teamwork, and creativity in the use of simulation teaching of concepts in chemistry to enhance students’ creativity skills. A descriptive and exploratory quantitative design was used in the study. The study used 150 serving chemistry teachers from the Calabar education zone public education system. A 29-item questionnaire was employed to gather data from respondents. Independent t-test, regression, and a 2-way analysis of variance were used for data analysis. Results obtained indicated high levels of teachers’ interest, literacy, self-efficacy, and teamwork in the utilization of simulation strategy in teaching chemistry concepts. Results of a 2-way analysis indicated that teachers’ age and years of experience influence teachers’ self-efficacy, teamwork, and creativity. It was recommended among others that serving teachers’ interest in the use of simulation is encouraged to support their learners’ instructional activities in a simulated classroom.
... They believe that creativity affects human's health and well-being (Richard, 2010;Corner, Silvia, 2015;Benedek, Bruckdorfer & Jauk, 2019). During and after creativity process, people feel happier, more active, relieved, relaxed, and satisfied (Silvia, et al., 2014;Conner, DeYoung & Silvia, 2017). On the contrary, people achieve greater creative effectiveness when they feel energetic, excited, enthusiastic, and joyful (Benedek, Bruckdorfer & Jauk, 2019;Elisondo, Vargas, 2019). ...
Full-text available
We are very happy to publish this issue of the International Journal of Learning, Teaching and Educational Research. The International Journal of Learning, Teaching and Educational Research is a peer-reviewed open-access journal committed to publishing high-quality articles in the field of education. Submissions may include full-length articles, case studies and innovative solutions to problems faced by students, educators and directors of educational organisations. To learn more about this journal, please visit the website We are grateful to the editor-in-chief, members of the Editorial Board and the reviewers for accepting only high quality articles in this issue. We seize this opportunity to thank them for their great collaboration. The Editorial Board is composed of renowned people from across the world. Each paper is reviewed by at least two blind reviewers. We will endeavour to ensure the reputation and quality of this journal with this issue.
As interest in creativity explodes, it has become more complicated to decide how to best nurture creativity in our schools. There are the controversial Common Core Standards in many states. Meanwhile, the classroom has become increasingly digital; it is easier to access information, communicate ideas, and learn from people across the world. Many countries now include cultivating creativity as a national educational policy recommendation, yet there is still debate over best practices. Indeed, many well-intentioned educators may institute programs that may not reach the desired outcome. The notion that schools 'kill creativity' has become a widespread social meme. We view such beliefs as both hyperbolic and problematic: they allow us to recognize there is a problem but not solve it. In this book, a wide array of international experts addresses these issues, discussing theories and research that focus on how to nurture creativity in K-12 and college-level classrooms.
How do we know what we know about creativity? This article argues for the importance of specification in defining different aspects of creativity (e.g., creative potential vs. creative behavior) and how they are measured (self-reported vs. externally judged, length of assessment) when making conclusions about creativity-relevant traits and processes. This methodological and conceptual point is illustrated with examples from the study of creativity and emotion. The conclusions about creativity and emotion will depend on specific measures used because different measures capture psychologically distinct aspects of creativity. The article focuses on measures of three aspects of creativity – performance on divergent thinking tests, self-perceived creativity, and reports of creative behavior and achievement. Specific emotion-related predictors are most relevant to different aspects of creativity based on the nature of predictors and outcomes and the match between them. For example, emotion traits describe typical ways of feeling across time and situations and are best suited to predict creative behavior and achievement accrued over long periods of time (e.g., from a year to a lifetime). Without specifying aspects of creativity or referring to creativity as a unitary construct, conclusions drawn can be unhelpful or misleading. Implications for future research are discussed.
Recent studies have found the connections between cognitive reappraisals’ creativity and their regulatory efficacy. The present study proposed and tested a novel hypothesis on the function of cognitive reappraisals, especially creative ones. That is, whether they could positively alter negative emotional arousal toward unpleasant stimuli. To this end, two questions were investigated: (a) whether the creative reappraisals were more capable than ordinary ones of transforming the negative stimuli (pictures) to be perceived as positive, and (b) whether these two kinds of reappraisals made the “negative‐to‐positive transformation” through different mechanisms. To answer the first question, we examined the power of the creative and ordinary reappraisals in making the “negative‐to‐positive transformation” using an indirect and delayed “positive‐or‐negative” picture‐sorting task (Exp. 1, n = 41 with a statistical power of 0.877), or using a direct and immediate subjective rating (Exp. 2, n = 31 with a statistical power of 0.768). To answer the second question, we checked how the factor of creativeness (creative vs. ordinary reappraisal) interacted with the factor of “timing” (simultaneous vs. delayed reappraisal delivery, Exp. 1), or with that of “dose” (one vs. three reappraisal applications; Exp. 2), in making the “negative‐to‐positive transformation,” respectively, and examined if the variation of “timing” or “dose” factors would exert different effects on the creative and ordinary reappraisals’ regulatory function. Our results generally proved that creative reappraisal was more capable of making the “negative‐to‐positive transformation” than the ordinary reappraisal, regardless of the direct and indirect emotion evaluation ratings as well as the variations in the timing and dose of reappraisal delivery. Moreover, we found that these two kinds of reappraisals could show dissociable dose‐dependent effects (but not timing‐dependent ones), thus partially implying that creative and ordinary reappraisal might make the “negative‐to‐positive transformation” through fundamentally different processes or mechanisms.
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Who gets chills—a pleasurable feeling of goose bumps—in response to music, and why? The current study used experience sampling to examine within-person variability in aesthetic chills. For one week, 106 undergraduate participants responded to 10 daily surveys, delivered via their cell phones, about their momentary activities, emotions, and environment, with an emphasis on whether they were listening to music and were experiencing chills. At the within-person level, music listening context and emotional states during music listening influenced whether or not people got chills. Chills were more likely when people listened to music that they chose and that they were listening to closely. Chills were also more likely when people were listening to music while happy or while sad, but not while worried. Overall, the study illustrates how music listening context and other within-person differences contribute to aesthetic chills in people’s everyday environments.
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Personal digital assistants (PDA), particularly Palm Pilots, are popular data collection devices in experience sampling research. The declining availability of such devices, however, has prompted researchers to explore alternative technologies for signaling participants and collecting responses. The present research considers interactive voice response (IVR) methods, which can deliver questions and collect data using common cell phones. Participants completed an experience sampling study using either a PDA (n = 428) or a cell phone under three different conditions (IVR condition n = 98; IVR Callback condition n = 93; IVR Callback Comeback condition n = 94). We found that response rates were higher when people used PDAs (69%) than when they used their cell phones (IVR condition = 51%), but response rates increased when people could call back within a few minutes of missing a signal (IVR Callback condition = 58%) and had a face-to-face meeting with a researcher midweek (IVR Callback Comeback = 64%). The daily life ratings were similar across the conditions. The findings are encouraging for researchers interested in using IVR cell phone methods for ecological momentary assessment, but more work is needed to develop procedures or incentives that increase response rates.
Test scores of divergent thinking obtained between 1959 and 1972 were correlated with a variety of personality measures administered since 1980. In this sample of 268 men, divergent thinking was consistently associated with self-reports and ratings of openness to experience, but not with neuroticism, extraversion, agreeableness, or conscientiousness. Both divergent thinking and openness were also modestly correlated with Gough's (1979)empirically derived Creative Personality Scale. Several other personality variables mentioned in the literature were also examined; those that were associated with divergent thinking were also generally correlated with openness. These data suggest that creativity is particularly related to the personality domain of openness to experience.