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Psychology of Aesthetics, Creativity,
and the Arts
What Types of Daydreaming Predict Creativity?
Laboratory and Experience Sampling Evidence
Claire M. Zedelius, John Protzko, James M. Broadway, and Jonathan W. Schooler
Online First Publication, August 10, 2020. http://dx.doi.org/10.1037/aca0000342
CITATION
Zedelius, C. M., Protzko, J., Broadway, J. M., & Schooler, J. W. (2020, August 10). What Types of
Daydreaming Predict Creativity? Laboratory and Experience Sampling Evidence. Psychology of
Aesthetics, Creativity, and the Arts. Advance online publication.
http://dx.doi.org/10.1037/aca0000342
What Types of Daydreaming Predict Creativity? Laboratory and
Experience Sampling Evidence
Claire M. Zedelius and John Protzko
University of California, Santa Barbara
James M. Broadway
Lincoln Land Community College
Jonathan W. Schooler
University of California, Santa Barbara
Daydreaming— engaging in an internal stream of thought unrelated to the here and now—is often linked
to creativity; but not all daydreams are creative or lead to creative ideas. To better understand the
relationship between daydreaming and creativity, we distinguish between types of daydreaming that
differ in style or content (future planning, pleasant daydreaming, personally meaningful daydreaming,
unaware/unintentional daydreaming, sexual daydreaming, and fantastical daydreaming) and explore how
these types relate to creativity. To assess both individual differences in daydreaming style (i.e., as a
trait-like disposition) and fluctuations in daydreaming within individuals, we measure daydreaming in the
lab and have participants track their daydreaming outside the lab via smartphones over a 5-day experience
sampling period. In the laboratory, creativity is assessed via convergent and divergent thinking tasks,
self-reports of creative behavior, and a creative writing assignment in which participants write a short
fictional story. Outside the lab, participants report their creative behavior and inspiration at the end of
each day. Whereas we find no clear evidence that daydreaming is related to divergent thinking,
personally meaningful daydreaming predicts self-reported creative behavior and daily inspiration,
whereas fantastical daydreaming predicts creative writing quality and day-to-day creative behavior.
Moreover, daily fluctuations in future planning appear to be positively related to day-to-day creative
behavior. We discuss the implications of distinctions between trait-level predictors (what “type of
daydreamer” a person is) and state-level predictors (what type of daydream one engages in) in relation
to creative behavior and inspiration.
Keywords: mind wandering, imagination, creativity, experience sampling, fantastical daydreaming
“Mostly it starts with daydreaming” (Neil Gaiman, Author, on the
source of his creative ideas in Rehm & Gaiman, 2015).
The author Neil Gaiman is only one of many artists and inven-
tors who draw inspiration from their daydreams. Daydreaming,
also referred to as mind wandering (e.g., Killingsworth & Gilbert,
2010; McVay, Kane, & Kwapil, 2009; Smallwood & Schooler,
2006), task-unrelated thought (e.g., Smallwood & Schooler,
2006), stimulus-unrelated thought (e.g., Teasdale et al., 1995) or
self-generated thought (Andrews-Hanna et al., 2013), is here de-
fined as thinking about something other than the here and now,
being disengaged or “decoupled” from one’s surroundings or
current activities, and engaged in an internal stream of thought. A
person’s internal stream of thought is constrained only by the
limits of their imagination. We can dream up intricate alternative
realities and project ourselves into fantastical worlds, which lay the
foundation for awe-inspiring fantastical stories (as Gaiman does).
Or we can mentally play out a myriad of different steps and
alternate paths to tackle a complicated problem. It is no wonder
daydreaming and creativity have often been treated as intimately
linked or overlapping constructs (e.g., Barr, Beaty, & Seli, 2018;
Christoff, Irving, Fox, Spreng, & Andrews-Hanna, 2016; Klinger,
2009; Singer, 1975; Singer & Schonbar, 1961; Singer, 2009;
Zedelius & Schooler, 2016; Zhiyan & Singer, 1997).
There is indeed evidence linking daydreaming to creativity. After
having worked on a difficult problem and having reached an impasse,
taking a break often leads to an unexpected boost in creativity, and lab
studies have shown this is especially the case when the break is spent
Claire M. Zedelius and XJohn Protzko, Department of Psychological
and Brain Sciences, University of California, Santa Barbara; James M.
Broadway, Department of Social Sciences and Business, Lincoln Land
Community College; Jonathan W. Schooler, Department of Psychological
and Brain Sciences, University of California, Santa Barbara.
This research was supported by Grant RFP-15– 09 from the Imagination
Institute (www.imagination-institute.org), and the John Templeton Foun-
dation (60844). The opinions expressed in this publication are those of the
authors and do not necessarily reflect the views of the Imagination Institute
or the John Templeton Foundation. Data available at: https://osf.io/njt4b/.
Correspondence concerning this article should be addressed to Claire M.
Zedelius, Department of Psychological and Brain Sciences, University of
California, Santa Barbara, CA, 93106. E-mail: claire.zedelius@psych
.ucsb.edu
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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
© 2020 American Psychological Association 2020, Vol. 2, No. 999, 000
ISSN: 1931-3896 http://dx.doi.org/10.1037/aca0000342
1
doing an undemanding activity that leaves room for frequent periods
of daydreaming (compared to a demanding task that prevents day-
dreaming; Baird et al., 2012; Leszczynski et al., 2017). More evidence
for this comes from research conducted outside the lab, tracking the
idea generation process of professional creative writers and elite
theoretical physicists (Gable, Hopper, & Schooler, 2018). The re-
search found approximately 20% of the writers’ and physicists’ cre-
ative ideas occurred to them during daydreaming episodes, that is,
when they were neither engaged in work nor actively pursuing a
work-related problem. In addition, a general disposition toward fre-
quent daydreaming has also been associated with increased creativity
(Baird et al., 2012; Zedelius & Schooler, 2015), and particularly with
spontaneous insights (Zedelius & Schooler, 2015).
But not all daydreams are creative, lead to creative solutions, or
provide inspiration for creative stories. Sometimes daydreams are
repetitive, obvious, boring, or even distressing. In fact, people
much of the time do not take pleasure from their daydreams
(Andrews-Hanna et al., 2013; Killingsworth & Gilbert, 2010;
Wilson et al., 2014) and the bulk of scientific findings paint a
picture of daydreaming as merely distracting, rather than produc-
tive (see Mooneyham & Schooler, 2013). Moreover, although
some studies have found positive evidence for the connection
between daydreaming and creativity, others have found no evi-
dence for it. Individual-differences studies examining how much
individuals mind wandered while taking a break from a creative
task, for instance, found mind wandering rates did not predict
subsequent creativity or improvements in creativity relative to
before the break (Smeekens & Kane, 2016). Indeed, some of the
positive evidence that has previously been found can be explained
by mechanisms that are not necessarily causal or reverse the
connection between daydreaming and creativity. The reason cre-
ative solutions often come to creative individuals during periods of
daydreaming (see Gable et al., 2018) may be that creative indi-
viduals like to daydream about creative problems when idle or
when engaged in less stimulating tasks. This would be in line with
findings from the individual-difference studies by Smeekens and
Kane (2016). Whereas they did not find evidence that mind wan-
dering rates in the lab predicted subsequent creativity, a trait scale
measuring daydreaming in everyday life showed a trending corre-
lation with creativity, and this was driven specifically by items
describing daydreaming when idle or during uninteresting tasks.
The inconclusive evidence so far raises several interesting ques-
tions: (a) Given daydreaming frequency does not robustly predict
creative performance, could there be a particular type of daydreaming,
a rare subset even, that is creatively productive? In other words, do
different types of daydreaming relate differently to creativity? (b) If
only particular types of daydreaming predict creativity, is this driven
by differences between individuals (i.e., more creative individuals
daydream in certain characteristic ways), or is there a within-person
association between daydreaming in a particular way and engaging in
creative behavior? The present research explores these questions.
Types of Daydreaming and Creativity
Daydreaming has long been recognized as an umbrella term
encompassing a variety of types of thought, differing in style and
content. The earliest research linking distinct types of daydreaming
to different outcomes (Singer & Antrobus, 1963; see also Huba &
Tanaka, 1983–1984) proposed daydreamers can be sorted into
three distinct styles of daydreaming: (a) positive-constructive day-
dreaming, characterized by pleasant and captivating daydreams
with vivid mental images, typically revolving around future plans
and creative ideas; (b) guilty-dysphoric daydreaming, revolving
around shame and guilt, fear of failure, but also fantasies of
heroism and achievements; and (c) poor attentional control, sum-
marized as frequent daydreaming and susceptibility to boredom
and distraction (Singer & Antrobus, 1963; see also Huba &
Tanaka, 1983–1984). Studies have found, among the three styles,
positive-constructive daydreaming is related to the personality trait
openness to experience (Blouin-Hudon & Zelenski, 2016; Zhiyan
& Singer, 1997), a trait that correlates strongly with lab measures
of creativity, including divergent thinking and idea generation
(Furnham & Bachtiar, 2008; King, Walker, & Broyles, 1996;
McCrae, 1987; McCrae & Costa, 1997; Silvia, Nusbaum, Berg,
Martin, & O’Connor, 2009), and with real-life creative behaviors
and achievements (Feist, 1998; Kaufman et al., 2016; McCrae,
1987; Silvia et al., 2009). Thus, this is first—though indirect—
evidence that distinct types of daydreaming relate differently to
creativity.
It is worth noting, however, that the three daydreaming styles
were conceived to be multifaceted patterns of thoughts, attitudes,
and behaviors, including not just strictly daydreaming-related ten-
dencies. Positive-constructive daydreaming notably includes inter-
personal curiosity and creative thinking, both of which are also
characteristics of openness to experience (McCrae, 1987; McCrae
& Costa, 1997; Silvia & Sanders, 2010) and creativity. Thus, to
better understand how types of daydreaming relate to creativity, it
is important to study different contents and styles of daydreaming
in isolation, without confounding them with other traits or behav-
iors, especially ones that are themselves linked to creativity.
Research looking more closely at daydreaming content has
found the majority of daydreams involve episodic thought in
which the daydreamer projects themselves into a simulated scene
(Song & Wang, 2012). Moreover, the majority of daydreams
revolve around current concerns (Kane et al., 2007; Kane et al.,
2017; Klinger, 1987, 1999; McVay et al., 2009) and plans for
upcoming tasks and activities (Baird, Smallwood, & Schooler,
2011; Morsella, Ben-Zeev, Lanska, & Bargh, 2010; Smallwood,
Nind, & O’Connor, 2009). Thus, when we mentally decouple from
our mundane day-to-day activities, we mostly escape to other
mundane day-to-day activities. A smaller proportion of daydreams
can be described as unusual or “fanciful,” involving hypothetical,
unlikely or fantastical scenarios, either as imaginary wish-
fulfillment or playful exploration (Klinger, 1978 –1979; Klinger,
1987–1988; Klinger, 2009; Singer, 2009). Although conceivably
even the most mundane of daydreams might be productive for
solving day-to-day problems (e.g., “What to do with children on
rainy days?” Singer, 2009), might this rarer type of fanciful or
fantastical daydreaming, which can transport us to far-away places
and alternative realities, offer a unique source of creative inspira-
tion?
One study that speaks to this question is a week-long experience
sampling study that linked different kinds of daydream reports to
individual differences in personality (Kane et al., 2017). Partici-
pants were probed at random moments throughout the day and
asked to rate the contents of their task-unrelated thoughts along
several dimensions: Planning (i.e., thinking about things to do), a
focus on worries or problems, a focus on things going on in the
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2ZEDELIUS, PROTZKO, BROADWAY, AND SCHOOLER
immediate surroundings, and fantasy content. Higher fantasy con-
tent was associated with greater openness to experiences, which
has been treated as a proxy for creativity. Thus, though still
indirect, this finding provides evidence that engaging in more
fantastical daydreams may be related to greater creativity. Further
supporting this possibility, greater ability to vividly imagine distal
scenarios (e.g., imagine what the world will be like in 500 years;
imagine being on the bottom of the ocean) is associated with more
creative idea generation and professional creative and artistic
achievements (Meyer, Hershfield, Waytz, Mildner, & Tamir,
2019). However, participants were instructed to imagine unlikely
or fantastical scenarios, these scenes did not occur to them spon-
taneously. Thus, it is an open question whether a natural proclivity
for fantastical daydreaming in day-to-day life is linked to creativ-
ity.
Aside from daydream content, researchers have distinguished
between other interesting dimensions, such as affect and aware-
ness. Daydreams can be pleasant or unpleasant (Huba, Aneshensel,
& Singer, 1981; Killingsworth & Gilbert, 2010; Kane et al., 2017),
more or less personally meaningful (Andrews-Hanna et al., 2013),
and the daydreamer can be aware or unaware of the fact that they
are daydreaming, that is, they can daydream with or without
“meta-awareness” (Christoff, Gordon, Smallwood, Smith, &
Schooler, 2009; Schooler, 2002). Moreover, a growing literature
now distinguishes between spontaneous and deliberate daydreams
(Christoff et al., 2016; Seli, Carriere, & Smilek, 2015; Seli, Risko,
& Smilek, 2016).
Most of these dimensions have never been studied in relation to
creativity. Only one study has examined deliberate and spontane-
ous daydreaming in relation to creativity and found a greater
tendency for deliberate daydreaming (i.e., agreement with items
such as, “I allow myself to get absorbed in a pleasant fantasy”) was
associated with increased creative performance, whereas a ten-
dency for spontaneous daydreaming (e.g., “I find my thoughts
wandering spontaneously”) was unrelated to creativity (Agnoli,
Vanucci, Pelagatti, & Corazza, 2018). This suggests that the type
of daydreaming that either leads to creative ideas or is itself the
result of creative thinking is more intentional. It is not clear
whether this is due directly to intentionality or to potentially
related factors, such as the perhaps more pleasant, interesting, or
fantastical thought content that could be associated with inten-
tional daydreaming. To better understand which types of day-
dreaming are particularly related to creativity, we take a slightly
different approach, and compare multiple daydream dimensions at
the same time, to test which ones independently contribute to
predicting differences in creativity.
The Current Research
Daydreaming
An important theoretical and methodological consideration for
the present study was that daydreaming can be conceptualized both
as a trait-like disposition of an individual (interindividual varia-
tion), and as a state differing from one moment to the next, much
like emotions (intraindividual variation). These definitions are not
necessarily independent—assuming a person’s general disposition
reflects a central tendency of an accumulation of states (see
Fleeson, 2004). A momentary experience, however, can nonethe-
less be wholly uncorrelated with one’s general disposition (see
Hao, Wu, Runco, & Pina et al., 2015). Considering both state and
trait aspects can offer unique insights into how daydreaming
relates to creativity. Focusing on daydreaming as a state can offer
insights into the mechanisms by which engaging in a daydream
can affect subsequent creative processes such as idea generation or
creative behavior. Treating daydreaming as a trait can offer in-
sights into how being a particular kind of daydreamer relates to
longer-term outcomes, such as a history of creative pursuits and
achievements. This association might not necessarily be causal but
could be caused by other latent variables. Moreover, it is possible
that engaging in a particular kind of daydream and being a par-
ticular kind of daydreamer relate differently to the same outcomes,
much like, for instance, running increases the risk of heart attack,
whereas being a runner is associated with reduced heart attack
risk. To account for these different levels of effects, we wanted to
examine different types of daydreaming both at the trait and at the
state level.
Because no existing daydreaming scale was available that could
function equally at the trait and state level, we conducted pilot
studies to construct a novel daydreaming scale that could do so.
The scale had to be short enough to be suitable for experience
sampling and strictly describe style and content of daydreaming
episodes, as opposed to other types of thinking or personality
traits. We then conducted a two-part study, which included a
laboratory session and a 5-day experience sampling period, in
which we assessed individual differences and within-subjects fluc-
tuations in daydreaming and creativity. These levels of measure-
ment allowed us to distinguish to what degree engaging in a
particular type of daydreaming and being a particular type of
daydreamer is associated with aspects of creativity.
Creativity
Like daydreaming, creativity is a heterogeneous concept. The
literature often defines it in terms of the capacity to generate novel
and useful ideas or solve problems by finding uncommon solutions
(Boden, 1994; Kampylis & Valtanen, 2010; Mumford, 2003;
Runco, 1988). In keeping with this definition, we included classic
measures of idea generation (generating novel uses for common
objects) and problem solving (solving compound remote associ-
ates problems), as well as self-reports of day-to-day creative be-
havior and inspiration. Although these are all important aspects of
creativity, another, particularly salient and meaningful aspect of
creativity is artistic expression. Here we were especially interested
in creative writing. There are reasons to suspect creative writing
may benefit especially from daydreaming. Coming up with a
fictional story, characters, and hypothetical or impossible events
are examples of mentally simulating things not currently present.
Moreover, compelling creative writing that captivates the reader
relies on bringing to life vivid and specific mental images, sounds,
smells, and emotions (Tankard & Hendrickson, 1996). Thus, in-
dividuals who frequently get absorbed in daydreams, especially the
types of unusual or fantastical daydreams involving distal simula-
tions of hypothetical or unlikely events (as opposed to mundane
plans for the next upcoming task or the next day), might also be
able to strategically harness this ability to bring compelling stories
to paper.
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3
WHAT TYPES OF DAYDREAMING PREDICT CREATIVITY
In sum, our goal was to get a nuanced view of the relationship
between daydreaming and creativity by examining how individu-
als differ from each other in the way they daydream, as well as
how their daydreams can fluctuate from one moment to another,
and then linking these differences and fluctuations to differences in
idea generation, problem solving, creative behavior and inspira-
tion, and artistic expression in the form of creative writing. We
begin by briefly summarizing the findings of our three pilot studies
and then present our main study, in which we explored these
questions.
Pilot Studies
The studies were approved by the University of California,
Santa Barbara’s (UCSB’s) internal review board and conducted in
accordance with the Declaration of Helsinki. To develop a com-
pact trait-and-state-daydreaming scale, we started with a large
preliminary scale that included items from widely used existing
daydreaming scales: the Short Imaginal Process Inventory (Huba
et al., 1981), the Self-Generated Thought Questionnaire (Andrews-
Hanna et al., 2013), and the Deliberate Versus Spontaneous Mind
Wandering Scale (Carriere, Seli, & Smilek, 2013). We only in-
cluded items that could function as a descriptor for a trait-like
disposition as well as a state. We further included newly generated
items we thought addressed gaps in existing scales. In two pilot
studies conducted through mTurk (Pilot 1: N⫽195, Pilot 2: N⫽
245), we asked participants to briefly describe their most recent
daydream and then to evaluate the content and style of the day-
dream using our large preliminary pool of items. (In Pilot 1, this
comprised 109 items, in Pilot 2 we expanded the item pool to 135
items based on some of the open-ended reports collected in Pilot 1
and based on the observation that few existing items captured
fantastical daydream content).
To reduce the number of items and derive a small number of
meaningful dimensions, we conducted an exploratory factor anal-
ysis on the data from Pilot 1 and, in an iterative process, eliminated
items not loading strongly onto any factor, showed high cross-
loadings on several factors, or did not fit for theoretical reasons.
We derived five interpretable factors. In Pilot 2, the same five
factors were reproduced, plus one additional factor consisting of
the newly added items, which we describe below as “fantastical
daydreaming.”
To derive a final short scale, we kept only the three highest-
loading items per factor, resulting in an 18-item scale (see Table 1
for the full scale) with the following factors: (a) future planning
(e.g., “I was thinking about things that might happen a short time
from now”), (b) pleasant daydreaming (e.g., “The daydream pro-
vided me with pleasant thoughts”), (c) meaningful daydreaming
(e.g., “I daydreamed about something that is of great value or
importance to me”), (d) sexual daydreaming (e.g., “I daydreamed
about somebody I desire sexually”), (e) unaware/unintentional
daydreaming (“For a while, I was not aware of the fact that I was
daydreaming”) and (f) fantastical daydreaming (e.g., “I day-
dreamed about something supernatural”; note this factor and the
corresponding items were not present in Pilot 1).
In Pilot 3, with a sample of 621 American adults matched to the
adult population in terms of demographics recruited through
the survey platform CriticalMix, we administered a trait-version of
the new daydreaming scale, in which items were rephrased to refer
to “daydreams” generally (e.g., the item “The daydream provided
me with pleasant thoughts” was rephrased as “My daydreams
provide me with pleasant thoughts”). We randomly split the sam-
ple into two sets and conducted confirmatory factor analyses to
reproduce the six factors that had been identified in exploratory
factor analyses on items in Pilot 2. The model fit was acceptable
in both data sets (Set 1: N⫽310,
2
⫽303.3, CMIN/df ⫽2.53,
comparative fit index [CFI] ⫽.89, root mean square error of
approximation [RMSEA] ⫽.07; set 2: N⫽311,
2
⫽328.7,
CMIN/DF ⫽2.74, CFI ⫽.90, RMSEA ⫽.08), thus establishing
the trait version of the daydreaming scale. See Table 2 for trait
items and factor loadings and Table 3 for covariances.
Our first pilot studies also provided some preliminary evidence
for a connection between certain daydreaming styles and creativ-
ity. In pilot studies 1 and 2, we also administered the Creative
Behavior Inventory (CBI) short form (Dollinger, 2003), a self-
Table 1
State Daydreaming Items
Subscale Items
Planning I was thinking about things that might happen a short time from now
I was thinking about things that might happen in a few days
I was thinking about the immediate practical consequences of something
Pleasant The daydream provided me with pleasant thoughts
The daydreams left me with warm, happy feelings
The daydream contained events that upset me (R)
Meaningful The daydream did not have any significance for me (R)
The daydream was very meaningful for me
I daydreamed about something that is of great value or importance to me
Unaware I was hardly aware of the fact that I was daydreaming
For a while, I was not aware of the fact that I was daydreaming
I was daydreaming unintentionally, without necessarily wanting to
Sex I was vividly imagining a sexual fantasy
I daydreamed about somebody I desire sexually
I was thinking about sex
Fantastical I daydreamed about something supernatural
The ideas that came to me during the daydream were funny and bizarre
I was imagining fantasy creatures or people
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4ZEDELIUS, PROTZKO, BROADWAY, AND SCHOOLER
report measure designed for a lay population and assessing cre-
ative behaviors and accomplishments in the visual and literary arts,
performing arts, and crafts (see Methods for more details). In Pilot
1, a regression analysis predicting creative behavior from the 5
initial daydreaming types (excluding fantastical daydreaming
which was not administered) identified meaningful daydreaming
(⫽.151, p⫽.048) and future planning (⫽.197, p⫽.006) as
significant predictors (overall model, F[5, 189] ⫽3.45, p⫽.005).
In Pilot 2, a regression analysis predicting creative daydreaming
from all six daydreaming types identified meaningful daydreaming
(⫽.192, p⫽.004) and fantastical daydreaming (⫽.195, p⫽
.003) as significant predictors (overall model, F[6, 238] ⫽3.073,
p⫽.006). Though preliminary, these pilot results were encourag-
ing in suggesting different types of daydreaming do relate differ-
ently to creativity—personally meaningful and fantastical day-
dreaming, as well as daydreaming revolving around future plans,
may be promising candidates for daydreaming styles likely to be
associated with creativity.
Main Study
The data collection for this study was done in two parts. The
first was a laboratory session, in which we assessed trait day-
dreaming and several measures of creativity. Participants com-
pleted two performance measures of creativity: the alternate uses
task as a measure of divergent thinking and compound remote
associates problems as a measure of problem solving or conver-
gent thinking. Performance on both tasks has previously been
found to be associated with frequent daydreaming (Baird et al.,
2012; Leszczynski et al., 2017; Zedelius & Schooler, 2015). We
did not have any hypotheses as to which daydreaming scales might
be related to these performance measures. We further administered
the same self-report scale of creative behaviors used in our pilot
studies. Based on the pilot studies, we predicted meaningful day-
dreaming, and potentially also fantastical daydreaming and plan-
ning, would emerge as predictors of this measure. We further gave
participants the chance to express their artistic creativity in the lab
by giving them a creative writing assignment: Participants were
given 20 min to write a short story based on a writing prompt. We
expected creative writing might particularly benefit from fantasti-
cal daydreaming, since coming up with a fictional story and
vividly bringing it to live would likely rely on similar mental
simulation processes as fantastical daydreaming.
After the laboratory session, participants were invited to
participate in a 5-day experience sampling period, in which we
Table 2
Trait Daydreaming Scale (Pilot 3)
Factor Items
Standardized
regression weights
sample 1
Standardized
regression weights
sample 2
Standardized
regression weights
in main study—
lab sample
Planning I think about things that might happen in the near future .804 .836 .749
I think about things that might happen in the next few days .756 .694 .812
I think about the immediate practical consequences of things .256 .453 .563
Pleasant My daydreams provide me with pleasant thoughts 1.021 .831 .912
My daydreams leave me with warm, happy feelings .599 .762 .899
My daydream contains events that upset me (R) .204 .069 .059
Meaningful My daydreams do not have any significance for me (R) .223 .421 .453
My daydreams are very meaningful for me .658 .782 .820
I daydream about things that are of great value or importance to me .707 .722 .752
Unaware While I daydream, I am hardly aware of it .732 .623 .818
When I start to daydream, I remain unaware of it for a while .749 .872 .719
I daydream unintentionally, without necessarily wanting to .552 .426 .790
Sex I vividly imagine sexual fantasies .837 .885 .914
I daydream about somebody I desire sexually .892 .873 .932
I daydream about sex .921 .905 .815
Fantastical I daydream about supernatural things .673 .714 .732
The ideas that come to me during daydreams are funny and bizarre .534 .545 .604
I imagine fantasy creatures or people .720 .802 .920
Table 3
Covariances Between Factors of Daydreaming. Below Diagonal Is Sample 1, Above Diagonal Is Sample 2
Factor covariance 1 2 3456
1. Planning .134 (.028) .096 (.023) .106 (.036) .044 (.03) .016 (.013)
2. Pleasant .034 (.013) .205 (.039) .279 (.059) .193 (.052) .006 (.021)
3. Meaningful .033 (.013) .079 (.027) .113 (.04) .119 (.038) .026 (.015)
4. Sex .029 (.023) .144 (.042) .07 (.03) .572 (.091) .122 (.039)
5. Fantastic .018 (.019) .077 (.032) .065 (.027) .491 (.09) .175 (.042)
6. Unaware .026 (.014) .01 (.02) .011 (.013) .12 (.055) .215 (.052)
Note. Bold numbers are statistically significant. Standard errors are in parentheses.
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5
WHAT TYPES OF DAYDREAMING PREDICT CREATIVITY
assessed types of daydreaming by probing participants at pseu-
dorandom moments throughout the day via their smartphone.
Upon being probed, participants were first asked what they had
been doing prior to being probed and whether they had been
daydreaming, and then to rate their most recent daydream on a
number of items. At the end of each day, participants were
asked about their creative behavior that day. Previous experi-
ence sampling research in which students were probed repeat-
edly and asked about their creative behavior throughout the day
has shown that students reported doing something creative 22%
of the time they were probed (Silvia et al., 2014). Thus, we were
confident that participants would be able to report on their
day-to-day creative behavior. At the end of each day, we also
asked participants how inspired they felt that day. Inspiration is
a motivational state that can energize the actualization of cre-
ative ideas, and has been linked to various kinds of creative
performance and artistic expression (Thrash, Maruskin,
Cassidy, Fryer, & Ryan, 2010).
Based on the preliminary results from our pilot studies, we
expected that meaningful daydreaming, fantastical daydreaming
and planning would be the most likely candidates to predict
creative behavior and inspiration. However, it was an open
question whether this would manifest at the trait or state level.
As we explain in detail below, by analyzing the experience
sampling data using a multilevel approach, in which we com-
pare a participant’s daydreaming scores to those of other par-
ticipants as well as to their own scores on other days, we can
distinguish between trait- and state-level predictions of differ-
ent daydreaming types. In other words, we can distinguish, for
instance, to what extent both engaging in fantastical daydreams
and being a “fantastical daydreamer” is associated with day-to-
day creative behavior and inspiration.
Method
The study was approved by the university’s internal review
board and conducted in accordance with the Declaration of
Helsinki. We report how we determined our sample size, all
data exclusions (if any), all manipulations, and all measures in
the study (see Simmons, Nelson, & Simonsohn, 2012). Some of
the data described in the methods and results have been previ-
ously reported in another publication (Zedelius, Mills, &
Schooler, 2019, Study 1). That publication describes the vali-
dation of the rubric we used to evaluate the creativity of the
short stories participants wrote as well as how these evaluations
correlate with the other creativity measures in this study.
Participants
For the laboratory component, 133 psychology undergraduate
students were recruited from the UCSB campus (88 female,
mean age ⫽19.3, SD ⫽1.4). The UCSB undergraduate student
population ranks above average in racial and ethnic diversity
(36% white, 28% Chicano/Latino, 28% Asian/Pacific Islander,
5% Black or African American, 1% American Indian or Alaska
Native), with 42% of students being on their way to becoming
first generation college graduates (University of California,
Santa Barbara, n.d.). Participants were compensated with
course credit. Of the 133, 89 further took part in the experience
sampling component (61 female, one did not indicate, Mage ⫽
19.4, SD ⫽1.4). For experience sampling data analyses, we
dropped participants with fewer than 8 thought-probe re-
sponses, leaving 65 participants in the final analyses (43 fe-
male, Mage ⫽19.41, SD ⫽1.4). Our desired sample size was
130 (similar to or exceeding those of Franklin et al., 2013; Kane
et al., 2007; Marcusson-Clavertz, Cardeña, & Terhune, 2016;
McVay et al., 2009), but was limited by participants’ interest in
volunteering in the relatively time intensive experience sam-
pling procedure.
Measures and Procedures
Upon entering the lab, participants were brought into indi-
vidual rooms where they completed behavioral creativity mea-
sures (the alternate uses task and the compound remote associ-
ates task; Mednick, 1962) and the CBI short form in fully
counterbalanced order (i.e., six orders: ABC, ACB, BAC, BCA,
CAB, CBA). This was followed by our trait-daydreaming scale
and the Mindful Attention and Awareness Scale. Next, we
collected demographic data, then participants performed a cre-
ative writing assignment. All measures were completed on the
computer.
Trait-daydreaming scale. Participants were provided with
the following definition of daydreaming: “Daydreaming is
when you stop attending to your current task or environment
and start thinking about other things (e.g., things that are
absent, in the past or future, or imaginary). Daydreaming is not
by definition positive. It can contain positive thoughts as well
as negative thoughts or worries. Daydreaming also is not by
definition deliberate. You can daydream without meaning to,
and sometimes without being aware of it. Daydreaming is very
common and normal, not to be confused with anything you
would seek treatment for. You will now read a number of
statements that describe possible contents and qualities of day-
dreams. Please indicate for each statement to what extent it
applies to your typical daydreams.” Participants then responded
to the 18 daydreaming items using a 6-point Likert scale,
ranging from 1 (definitely untrue)to6(definitely true).
Mindful Attention and Awareness Scale. The Mindful At-
tention and Awareness Scale (MAAS; Brown & Ryan, 2003), a
15-item scale that measures self-reported absent-minded behav-
ior, was included as a measure of daydreaming frequency. The
scale was reverse-coded so higher scores reflect greater absent-
mindedness. Cronbach’s alpha was .90. Although the focus of
the current study was on daydreaming styles and contents, we
report correlations between the MAAS and our dependent vari-
ables.
CBI short form. This 24-item scale was designed to mea-
sure common creative behaviors and accomplishments in a lay
population. The items describe activities in the visual, literary,
and performing arts, and crafts (e.g., “Designed and made your
own greeting cards”; “Wrote a play [excluding school or uni-
versity course work]”; “Had a piece of literature (e.g. poem,
short stories, etc.) published in a school or university publica-
tion”). Participants responded how often they have done each
activity in their adolescent and adult life using a 4-point Likert-
type scale, ranging from 1 (never did this)to4(more than five
times). Cronbach’s alpha was .90.
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6ZEDELIUS, PROTZKO, BROADWAY, AND SCHOOLER
Alternate uses task (Guilford, 1967; Torrance, 2008).
Participants were asked to come up with “as many unusual and
creative uses as you can think of” for a tin can and a cardboard
box (order counterbalanced), the only restriction being that the
uses should be realistically doable (i.e., the object can really be
used in the described way) and that they had to be genuine uses
(e.g., “throw it into the ocean”, would not be a genuine use,
since you can throw anything into the ocean and this action
alone isn’t of any use.) Participants were given 90 s per object
to generate ideas. After listing uses, participants were also
asked to select their most creative idea for each object. Re-
sponses were scored subjectively by two independent raters for
fluency (the number of valid ideas, i.e., ideas that constituted
genuine uses relevant to the object, according to raters) and
originality (i.e., whether the raters deemed an idea creative,
surprising, or novel, scored as either 0 [not original]or1
[original]). Raters were told not to be too strict (e.g., a tin can
cut into rings might not make for a very good bracelet, but it can
be done). Following the recommendation by Hallgren (2012),
the raters first evaluated 30% of the data. After establishing
adequate interrater reliability (intraclass correlation [ICC; flu-
ency] ⫽.795, ICC [originality] ⫽.731), one rater continued to
evaluate responses for the tin can, the other responses for the
cardboard box. Finally, valid ideas and originality scores were
summed up to generate total scores for fluency and originality
for the entire task. (We did not divide originality by fluency
because we did not want to penalize participants for listing a
number of uncreative ideas along with creative ideas; see Silvia
et al., 2008. Note: Fluency and originality scores were inter-
correlated. Fluency correlated with overall originality, r⫽.627,
p⬍.001, but not originality of the two responses selected as
best ideas, r⫽⫺.084, p⫽.39.)
Compound remote associates task. On each trial, partici-
pants were shown three words (e.g., “board, magic, death”), and
were asked to find a fourth word that can be combined with
each word in the set to form a compound word or phrase (e.g.,
“black”, as in, “black board”, “black magic”, “black death”).
Participants received 32 problems total. For each problem, they
were given 30 s to indicate via button press when they had
found the solution. After pressing the button, they had 10 s to
type in their answer.
Creative writing assignment. Participants were asked to
write a short fictional story based on a writing prompt. The
prompt read, “Create a character who has suddenly and unex-
pectedly attained some sort of power. In the wider perception of
the world the level of authority may be small or great, but for
this person, the change is dramatic. Write about the moment in
which your character truly understands the full extent of his or
her newfound power for the first time.” Participants were given
20 min to write and edit their story as they saw fit. The stories
were independently evaluated by six raters (including the first
author and trained students from the Psychology and English
departments) using a rubric that assessed three dimensions:
Image, Voice, and Story Originality.
Image describes the degree to which the writing evokes rich,
concrete mental images. Writing high in Image contains several
vivid and concrete visual images, sounds, smells, physical sensa-
tions, emotions, and/or direct thought and speech. (e.g., “I could
smell the cigarettes on his breath, which choked the little life out
of my pitiful existence. Time had seemed to stop for me then, and
I could feel the pain of the many times before this, where the smell
of cigarettes invaded my senses, and I choked as a knife was held
against my skin.”) Writing low in image contains no or very few
concrete details and mental images. (e.g., “I could tell he had
smoked.”)
Voice describes the degree to which the writer has created their
own unique, recognizable voice or style, for instance by using
stylistic tools or a unique narrative perspective. Writing high in
Voice contains several stylistic tools such as rare words, interest-
ing sentence structures, metaphors or similes, or a unique narrative
perspective or attitude such as humor, irony, wittiness, or darkness.
(e.g., “It was a pitiful existence, and it led to this day, where blood
was meant to leak upon the pavement, and my life was to end. [. . .]
I reached out to him, and reaped his soul straight from his body,
tearing through his chest with my grim hands, all in a dark mist,
which resonated from the ground. The next words came through
from a memory long ago: ‘I am death, the destroyer of worlds,’
and with that a scythe materialized in a purple mist, and my eyes
grew dark. I realized what I had been given, a power to correct the
evils of man, to fight like my uncle did long ago. In my death, the
reaper was born.”) Writing low in Voice contains no or very few
stylistic tools and does not have an identifiable or unique narrative
style.
Story Originality describes the degree to which the story idea or
plot is novel and original. An original story does not resemble
other stories in the sample or widely known stories from books or
movies. Highly original stories were often surprising to the raters
and described characters who experienced unexpected events or
discovered interesting, unusual realistic or fantastical powers (e.g.,
political power or the power to communicate with animals). An
unoriginal story strongly resembles other known stories or stories
from other participants. (e.g., many students wrote about a college
student who, during an interaction with a love interest on campus,
discovers they suddenly, without reason or explanation, have
gained the power to hear other people’s thoughts.)
Stories were rated by each rater as poor (coded as 1), fair (coded
as 2), or good (coded as 3) on each dimension. A poor rating was
given when the story contained none or very few of the above-
listed characteristics (i.e., no or very few concrete details, no or
very few stylistic tools, no original idea or a only a minor deviation
from a known story), a fair rating was given when the story
contained some of the characteristics, and a good rating was given
when the story contained many of the characteristics. Raters
showed excellent reliability (the ICCs were .93 for Image, .92 for
Voice, and .90 for Originality). Scores from all six raters were then
averaged to derive three final scores for Image, Voice, and Story
Originality per participant that could range between 1 and 3. The
rubric and its correlates with the other creativity measures reported
here have been previously reported in another publication, in
which we used computational linguistic analyses to validate the
rubric (see Zedelius et al., 2019, Study 1).
Experience Sampling
After the lab session, participants were invited to also participate
in a follow-up experience sampling procedure. This part of the data
collection was done via a smartphone application (MetricWire).
Participants were shown how to use the application. The experi-
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7
WHAT TYPES OF DAYDREAMING PREDICT CREATIVITY
ence sampling procedure started the next day. When receiving a
notification or “thought probe” on their phone, participants would
hear their usual ring-tone for notifications and see a prompt on
their phone screen. They had the option to respond or actively
reject the probe. If an initial probe was ignored, another probe was
sent after 10 min to prompt another alarm tone. If this probe was
ignored, it would disappear from the screen after 10 min.
Participants were probed in this way eight times throughout
each day (not counting follow-ups and additional once-a-day
prompts—see below) between 9 a.m. and 9 p.m. Each time par-
ticipants were first asked, “What were you doing before you
received this notification?” and then, “Were you daydreaming in
the moment before you received this notification?” They were
reminded of the definition of daydreaming (“Daydreaming is when
you stop attending to your current task or environment and start
thinking about other things”) and could respond with yes or no.
They were then instructed as follows: “Think about your most
recent daydream. Continue to see a number of statements and
indicate how well each statement describes your most recent
daydream.”
We instructed participants to rate their “most recent” daydream,
regardless of whether they had been daydreaming or not immedi-
ately prior to being probed. This was to avoid the temptation for
participants to answer “no” to shorten their answer time. We only
analyzed data from the times participants answered that they were
daydreaming prior to being probed. Using a 5-point Likert scale,
ranging from 0 (definitely untrue)to4(definitely true), participants
rated their daydream using our 18-item (state) daydreaming scale.
At the end of each day (9:45 p.m.), participants received another
prompt with two questions: (a) “How creative were you today?
(Being creative includes coming up with novel or original ideas;
expressing oneself in an original way, or spending time doing
artistic activities (art, music, painting, writing, etc.)” Participants
answered on a 4-point Likert scale from 1 (not at all creative)to
4(very creative). (b) “How inspired did you feel today?” Partici-
pants answered on a 4-point Likert scale from 1 not at all)to4
(very much). Participants could delay responding until the morn-
ing.
Results
Laboratory Data (Trait Daydreaming)
Analytic approach and descriptive statistics. For each cre-
ativity measure administered in the laboratory that correlated sig-
nificantly with at least one daydreaming type, we ran a regression
analysis with the six daydreaming styles as predictors. (Factor
loadings of the trait daydreaming scale in the current sample are
shown in Table 2. Covariances are shown in Table 4. Descriptive
statistics, intercorrelations, and reliabilities of the trait daydream-
ing scale factors are shown in Table 5. Descriptive statistics of the
creativity measures and correlations with trait daydreaming types
as well as trait daydreaming frequency (as assessed with the
MAAS) are shown in Table 6, and intercorrelations between
creativity measures in Table 7.)
CBI Short Form. For creative behavior, the overall regres-
sion model was significant, F(6, 126) ⫽2.752, p⫽.015, R
2
⫽
.116. The complete regression results are shown in Table 8.
Personally meaningful daydreaming emerged as a significant
predictor. Moreover, there was a trend for fantastical daydream-
ing to predict creative behavior, but this was not statistically
significant.
Creative writing. For the creative writing task, we ran sepa-
rate regression analyses on the evaluation categories Image and
Voice as dependent measures (see Table 9). For Image, fantastical
daydreaming emerged as the only significant predictor, although
the overall model was only marginally significant, F(6, 126) ⫽
2.104, p⫽.057, R
2
⫽.091. For Voice as the dependent variable,
fantastical daydreaming emerged as the only significant predictor,
although again the omnibus model including all the nonsignificant
predictors was marginally significant, F(6, 126) ⫽1.927, p⫽
.081, R
2
⫽.084.
Experience Sampling Results
Analytic approach and descriptive statistics. Because the
experience sampling data have a hierarchical structure, with
multiple observations nested within participants, we used a
hierarchical linear modeling approach to analyze the data. This
also allowed us to disaggregate two types of statistical effects:
(a) effects of differences between individuals, for instance, a
participant showing a greater tendency toward meaningful day-
dreaming compared to other participants over the course of the
experience sampling period (i.e., the effect of being a “mean-
ingful daydreamer”); and (b) effects of daily fluctuations within
an individual, for instance a participant engaging in more
meaningful daydreaming on one day compared to other days
(i.e., the effect of engaging in meaningful daydreams).
To separate these effects, we conducted two multilevel
mixed-effects linear regression analyses, one with daily reports
of creative behavior and one with daily reports of inspiration as
dependent variables. The two dependent variables were corre-
lated; the within-participant correlation was r⫽.48, p⬍.001,
which can be considered a large correlation, but in our opinion
Table 4
Covariances Between Factors of Daydreaming in the Main Study
Factor covariance 1 2 3 4 5
1. Pleasant .205 (.115)
2. Meaningful .417 (.132) .147 (.102)
3. Sex .118 (.101) .150 (.093) .315 (.093)
4. Fantastic .183 (.103) .264 (.095) .20 (.104) .314 (.089)
5. Unaware .297 (.101) ⫺.080 (.107) .383 (.099) .212 (.095) .254 (.097)
Note. Bold numbers are statistically significant. Standard errors are in parentheses.
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8ZEDELIUS, PROTZKO, BROADWAY, AND SCHOOLER
not large enough to consider these measures redundant (see
Gignac & Szodorai, 2016). As there are multiple daydreaming
reports within each day, but only one end-of-day response per
participant, this means varying daydreaming reports throughout
one day predicted identical end-of-day responses for said day.
Each model was estimated with restricted maximum likelihood
estimation and included the following predictors: the person
means (calculated over the entire experience sampling period)
and person-mean centered individual observations of partici-
pants’ scores for the six daydreaming types (see Curran &
Bauer, 2011; Hoffman & Stawski, 2009). To person-mean cen-
ter individual observations, we likewise used the person mean
for the entire experience sampling period. We further included
a time variable as a covariate to account for temporal effects.
Our time variable was a thought-probe counter, which counted
up throughout the study; the counter counted the probes pre-
sented to the participant, regardless of whether the participant
responded to or ignored any of the probes. We included autore-
gressive errors. The analysis code is available on the Open
Science Framework (Zedelius, Protzko, Broadway, & Schooler,
2020; see https://osf.io/njt4b/).
The equations for both analyses are shown below. Not that
the ending_pmc denotes a person mean centered variable and
the ending_pm denotes the person mean.
Creative_behaviorij ⫽
0j⫹
1jMeaning_pmcij
⫹
2jPlanning_pmcij ⫹
3jUnaware_pmcij
⫹
4jPleasant_pmcij ⫹
5jSex_pmcij
⫹
6jFantastic_pmcij ⫹
7jMeaning_pmij
⫹
8jPlanning_pmij ⫹
9jUnaware_pmij
⫹
10jPleasant_pmij ⫹
11jSex_pmij
⫹
12jFantastic_pmij ⫹
13jprobe_counterij
⫹eij (1)
0j⫽␥
00 ⫹u0j
Table 5
Descriptive Statistics, Intercorrelations and Reliability for Trait Daydreaming Types (Laboratory Data)
Variable
Cronbach’s
Alpha M(SD)1 2 3456
1. Planning .731 4.52
(0.94) — — — — —
2. Pleasant .552 4.13 r⫽.016
(0.74) p⫽.858 — — — —
3. Meaningful .708 3.84 r⫽.277 r⫽⫺.115
(1.12) p⫽.001 p⫽.189 — — —
4. Unaware .820 3.65 r⫽.217 r⫽⫺.170 r⫽.278
(1.18) p⫽.012 p⫽.050 p⫽.001 — —
5. Sex .917 3.53 r⫽.086 r⫽.010 r⫽.240 r⫽.188
(1.41) p⫽.327 p⫽.910 p⫽.005 p⫽.030 —
6. Fantastical .787 2.94 r⫽.160 r⫽.071 r⫽.160 r⫽.219 r⫽.267
(1.25) p⫽.066 p⫽.418 p⫽.066 p⫽.011 p⫽.002
7. MAAS (frequency) .897 3.246 r⫽.182 r⫽⫺.099 r⫽.265 r⫽.524 r⫽.268 r⫽.206
(0.918) p⫽.036 p⫽.259 p⫽.002 p⬍.001 p⫽.002 p⫽.018
Note. MAAS ⫽Mindful Attention and Awareness Scale.
Table 6
Descriptive Statistics of Creativity Measures and Correlations With Trait Daydreaming Types (Laboratory Data)
Variable M(SD) Planning Pleasant Meaningful Unaware Sex Fantastical MAAS
Story image 1.563 r⫽.006 r⫽⫺.089 r⫽.105 r⫽⫺.071 r⫽.114 r⫽.215 r⫽⫺.021
(0.595) p⫽.943 p⫽.309 p⫽.229 p⫽.419 p⫽.190 p⫽.013 p⫽.807
Story voice 1.801 r⫽⫺.052 r⫽.039 r⫽.123 r ⫽⫺.036 r⫽.068 r⫽.229 r⫽.059
(0.640) p⫽.550 p⫽.659 p⫽.160 p⫽.684 p⫽.437 p⫽.008 p⫽.499
Story originality 1.928 r⫽⫺.123 r⫽⫺.065 r⫽⫺.091 r⫽.004 r⫽.013 r⫽.046 r⫽.046
(0.636) p⫽.157 p⫽.460 p⫽.299 p⫽.964 p⫽.882 p⫽.595 p⫽.599
CBI 2.030 r⫽.124 r⫽⫺.050 r⫽.297 r⫽.114 r⫽.100 r⫽.207 r⫽.199
(0.701) p⫽.156 p⫽.565 p⫽.001 p⫽.192 p⫽.253 p⫽.017 p⫽.022
AUT fluency 3.571 r⫽.158 r⫽⫺.116 r⫽.131 r⫽⫺.039 r⫽⫺.148 r⫽⫺.024 r⫽⫺.078
(1.619) p⫽.069 p⫽.185 p⫽.132 p⫽.657 p⫽.088 p⫽.788 p⫽.374
AUT originality 1.782 r⫽.078 r⫽⫺.104 r⫽.054 r⫽⫺.015 r⫽⫺.145 r⫽.046 r⫽.017
(1.031) p⫽.370 p⫽.233 p⫽.539 p⫽.864 p⫽.096 p⫽.601 p⫽.847
Remote associates 0.539 r⫽⫺.094 r⫽⫺.021 r⫽.112 r⫽⫺.107 r⫽⫺.018 r⫽.015 r⫽⫺.129
(0.199) p⫽.281 p⫽.809 p⫽.198 p⫽.219 p⫽.841 p⫽.862 p⫽.140
Note. MAAS ⫽Mindful Attention and Awareness Scale; CBI ⫽Creative Behavior Inventory; AUT ⫽Alternative Use Task.
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9
WHAT TYPES OF DAYDREAMING PREDICT CREATIVITY
Inspirationij ⫽
0j⫹
1jMeaning_pmcij ⫹
2jPlanning_pmcij
⫹
3jUnaware_pmcij ⫹
4jPleasant_pmcij
⫹
5jSex_pmcij ⫹
6jFantastic_pmcij
⫹
7jMeaning_pmij ⫹
8jPlanning_pmij
⫹
9jUnaware_pmij ⫹
10jPleasant_pmij
⫹
11jSex_pmij ⫹
12jFantastic_pmij
⫹
13jprobe_counterij ⫹eij (2)
0j⫽␥
00 ⫹u0j
Over the experience sampling period, participants reported they
were daydreaming 63.44% of the time. All analyses are restricted
to when participants reported they were daydreaming. Table 10
shows descriptive statistics and intercorrelations for the six types
of daydreaming. Moreover, Table 11 shows intercorrelations be-
tween participants’ reports of their daydreaming styles during the
experience sampling period (averaged over all 5 days) and their
reports of the corresponding trait daydreaming styles in the lab.
The significant correlations indicate some correspondence be-
tween participants’ self-reports in the moment they are being
probed and their more removed judgments of their “typical” day-
dreaming tendencies when asked in the lab.
Creative behavior. Self-reports of day-to-day creative behav-
iors were predicted only by within-subjects fluctuations in the
daydreaming type future planning,b⫽.103 p⫽.011, 95% CI
[.024, .183]. No other daydreaming type significantly predicted
creative behavior at the within-subjects level. This suggests that
the act of daydreaming about future planning predicts self-reported
creative behavior. At the between-subjects level, creative behavior
was predicted only by individual differences in fantastical day-
dreaming, b⫽.596 p⫽.02, 95% CI [.092, 1.099]. No other
daydreaming style predicted creative behavior at the between-
subjects level. This suggests that fantastical daydreamers self-
report more creativity than others. All coefficients are shown in
Table 12.
Inspiration. Reports of feeling inspired were not significantly
predicted by within-subjects fluctuations in any of the daydream-
ing types. Inspiration was predicted only by between-subjects level
differences in personally meaningful daydreaming, b⫽.875 p⫽
.008, 95% CI [.204, 1.521]. All coefficients can be seen in Table
13.
Discussion
Daydreaming has often been linked to creativity, but clearly not
all daydreams are creative or lead to creative ideas. In the present
study, two types of daydreaming emerged as the most strongly
related to individual differences in creativity. Those were person-
ally meaningful and fantastical daydreaming. Individuals more
often engaging in meaningful daydreaming (relative to others)
reported having accumulated more artistic creative behaviors and
achievements over their life and reported greater levels of daily
inspiration over the course of the experience sampling period.
More often engaging in fantastical daydreaming, on the other
Table 7
Intercorrelations Between Creativity Measures
Story voice Story originality CBI AUT fluency AUT originality CRAT accuracy
Story image r⫽.638 r⫽.303 r⫽.222 r⫽.135 r⫽.245 r⫽.179
p⬍.001 p⬍.001 p⫽.010 p⫽.120 p⫽.004 p⫽.039
Story voice r⫽.413 r⫽.226 r⫽.171 r⫽.226 r⫽.223
p⬍.001 p⫽.009 p⫽.049 p⫽.009 p⫽.010
Story originality r⫽.006 r⫽.110 r⫽.179 r⫽.103
p⫽.948 p⫽.208 p⫽.039 p⫽.248
CBI r⫽.141 r ⫽⫺.006 r⫽.197
p⫽.105 p⫽.945 p⫽.023
AUT fluency r⫽.627 r⫽.206
p⬍.001 p⫽.017
AUT originality r⫽.105
p⫽.229
Note. MAAS ⫽Mindful Attention and Awareness Scale; CRAT ⫽Compound Remote Associates task; CBI ⫽Creative Behavior Inventory; AUT ⫽
alternative use task.From “Beyond Subjective Judgments: Predicting Evaluations of Creative Writing From Computational Linguistic Features,” by C. M.
Zedelius, C. Mills, and J. W. Schooler, 2019, Behavior Research Methods,51, p. 879. Copyright 2019 by Springer Nature.
Table 8
Regression Results for Daydreaming Styles on Creative Behavior Inventory Scores
Variable B SE tp 95% CI
Planning 0.020 .067 0.027 0.301 0.764 [⫺0.112, 0.152]
Pleasant ⫺0.032 0.082 ⫺0.033 ⫺0.386 0.700 [⫺0.193, 0.130]
Meaningful 0.165 0.058 0.263 2.860 0.005 [0.051, 0.280]
Unaware ⫺0.003 0.054 ⫺0.006 ⫺0.062 0.950 [⫺0.111, 0.104]
Sex ⫺0.004 0.044 ⫺0.008 ⫺0.094 0.925 [⫺0.092, 0.083]
Fantastical 0.094 0.050 0.116 1.857 0.066 [⫺0.006, 0.193]
Constant 1.186 0.494 2.400 0.018 [0.208, 2.164]
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10 ZEDELIUS, PROTZKO, BROADWAY, AND SCHOOLER
hand, was predictive of higher-quality creative writing in the lab
and reports of daily creative behavior over the experience sam-
pling period. Looking at intraindividual fluctuations in daydream-
ing over the course of several days, we found that only fluctuations
in the daydreaming type we labeled planning appeared to predict
creative behavior. That is, on days when participants reported
more daydreams revolving around plans than usual, they also
reported more creative behavior. Interestingly, being more of a
“planner,” compared to others, was unrelated to creative behavior.
These findings provide first insights into the types or contents of
daydreaming that may be more creatively productive. They also
illustrate the value of differentiating between operational defini-
tions of daydreaming as trait-like tendencies and states that fluc-
tuate within a person. The fact that day-to-day creative behavior
and inspiration were predicted by individual differences in fantas-
tical and meaningful daydreaming, respectively, but not by intra-
individual fluctuations, suggests these relationships are driven by
characteristics of the daydreamer, not the process of engaging in
fantastical or meaningful daydreams. That is, the kind of person
who is inclined to daydream in a way that is highly meaningful or
fantastical is likely to report high levels of creative behavior and
inspiration, but engaging in unusually high levels of meaningful or
fantastical daydreaming on a given day does not boost creativity.
This suggests the association between these daydreaming types
and creativity is not causal, but because of other latent variables,
for instance, differences in personality. Alternatively, these forms
of daydreaming may contribute to more temporally extended cre-
ative achievement. They may lead to creative solutions, but their
value may take a while to be integrated and thus is not reflected in
daily fluctuations in creativity.
For planning, on the other hand, we found the opposite pattern.
A general tendency toward daydreams revolving around plans is
not associated with creativity, but higher than usual reports of
planning were associated with a boost in creative behavior. This
could suggest this type of daydreaming can perhaps help motivate
creative behavior or turn ideas into actual creative pursuits. This
fits with Klinger’s current concerns hypothesis, according to which
daydreaming serves to pursue personal goals and concerns
(Klinger, 1999). It might also be that the daydreaming is a conse-
quence of current goals and concerns, rather than an instrumental
part in the goal pursuit. That is, on days on which people are more
focused on achieving goals, this goal striving may also cause them
to daydream more about their goals and plans.
Table 9
Regression on Creative Writing (Image and Voice)
Variable B SE Beta tp 95% CI
Image
Planning ⫺0.014 0.057 ⫺0.022 ⫺0.246 0.806 [⫺0.127, 0.099]
Pleasant ⫺0.101 0.070 ⫺0.125 ⫺1.435 0.154 [⫺0.240, 0.038]
Meaningful 0.050 0.050 0.093 0.996 0.321 [⫺0.049, 0.148]
Unaware ⫺0.089 0.047 ⫺0.177 ⫺1.909 0.059 [⫺0.181, 0.003]
Sex 0.028 0.038 0.066 0.730 0.467 [⫺0.048, 0.103]
Fantastical 0.112 0.043 0.234 2.578 0.011 [0.026, 0.197]
Constant 1.751 0.425 0 4.117 0.000 [0.909, 2.593]
]Voice
Planning ⫺0.075 0.062 ⫺0.110 ⫺1.215 0.227 [⫺0.197, 0.047]
Pleasant 0.019 0.076 0.022 0.257 0.798 [⫺0.131, 0.169]
Meaningful 0.084 0.054 0.146 1.559 0.122 [⫺0.023, 0.190]
Unaware ⫺0.055 0.050 ⫺0.101 ⫺1.092 0.277 [⫺0.155, 0.045]
Sex ⫺0.002 0.041 ⫺0.004 ⫺0.047 0.962 [⫺0.083, 0.079]
Fantastical 0.126 0.047 0.245 2.694 0.008 [0.033, 0.219]
Constant 1.575 0.459 3.431 0.001 [0.667, 2.484]
Table 10
Descriptive Statistics and Intra-Individual Correlations Between State Daydreaming Types (Experience Sampling Data)
Variable M(SD)1 2 3 4 5
1. Planning 1.95 — — — — —
(1.13)
2. Pleasant 2.47 r⫽⫺.065 — — — —
(1.05) p⫽.109
3. Meaningful 2.16 r⫽.246 r⫽.143 — — —
(1.02) p⬍.001 p⬍.001
4. Unaware 1.98 r⫽.191 r⫽.080 r⫽.091 — —
(1.23) p⬍.001 p⫽.046 p⫽.024
5. Sex 1.04 r⫽.025 r⫽.318 r⫽.170 r⫽.086 —
(1.29) p⫽.541 p⬍.001 p⬍.001 p⫽.032
6. Fantastical 0.82 r⫽⫺.074 r⫽.076 r⫽⫺.120 r⫽.084 r⫽.102
(0.98) p⫽.066 p⫽.060 p⫽.003 p⫽.037 p⫽.011
Note. Data represent only episodes when participants reported they were daydreaming at the moment prior to being probed.
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11
WHAT TYPES OF DAYDREAMING PREDICT CREATIVITY
To more definitively determine the possible role of meaningful,
fantastical and planning forms of daydreaming, future studies
should examine the outcome of experimental manipulations that
systematically encourage these types of daydreaming. Research
might also investigate how exactly meaningful or fantastical day-
dreamers differ from people who do not identify with those day-
dreaming types. The personality trait openness to experience is a
candidate that might mediate the relationship between fantastic
daydreaming tendencies and creative pursuits. Research has shown
openness to experiences, including a subscale describing enjoy-
ment of daydreams, unguided thoughts, and fantasies, correlates
with creative performance (Smeekens & Kane, 2016; Study 2).
Future research could investigate whether certain daydreaming
tendencies or enjoyment of daydreaming are an active ingredient
in openness that mediates its association with creativity.
Future research might also be usefully directed to further ex-
ploring differences between types of daydreaming and aspects of
creativity. Notably, none of the daydreaming types we measured
here predicted performance on the idea generation and convergent
thinking tasks. One explanation could have to do with the mea-
surement conditions. For divergent thinking, ideas get more cre-
ative over time (e.g., Beaty & Silvia, 2012; Christensen, Guilford,
& Wilson, 1957), and the relationship between daydreaming styles
and divergent thinking may only be detectible once individuals
have moved beyond generating ordinary ideas (which can simply
be retrieved from memory) and have started to generate truly
creative ideas. Longer trials might have allowed us to detect such
a nonlinear effect. A greater emphasis on the quality of ideas over
quantity might also have helped shift participants’ toward truly
creative thinking, which could have revealed a connection between
daydreaming and creative ideation, if this connection exists.
Alternatively, it is possible we only identified types of day-
dreaming predictive of artistic expressions of creative behavior,
not necessarily other aspects of creativity. Or daydreaming may be
more predictive of participants’ creative self-concept and motiva-
tion than their actual creative performance. It is worth pointing out,
though, that our measures of creative writing (at least the dimen-
sions Image and Voice) correlated with originality on the alternate
uses task and the compound remote associates task (the third
dimension, Originality, did not consistently correlate with other
creativity measures and is perhaps a less valid measure of creative
writing). Thus, at least Image and Voice can be considered per-
formance measures of creativity.
It is also possible that daydreaming content and frequency are
simply not robust predictors of how well the person performs on
idea generation or convergent thinking tasks. Although some pre-
vious studies have found a correlation between trait daydreaming
frequency and performance on divergent and convergent thinking
tasks (Baird et al., 2012; Zedelius et al., 2015), other studies have
found that daydreaming frequency measured with thought probes
was uncorrelated with subsequent performance on the alternate
uses task (Smeekens & Kane, 2016). The current study also fails to
observe any correlation between general daydreaming frequency
(assessed with the MAAS) and creative task performance. Yet
other studies suggest that daydreaming benefits these tasks through
Table 11
Correlations Between Trait Daydreaming Styles in the
Laboratory and State Daydreaming (Person Means) During the
Experience Sampling Period
Daydreaming
style
Trait–state
correlation
Planning r⫽.108, p⫽.394
Pleasant r⫽.535, p⬍.001
Meaningful r⫽.488, p⬍.001
Unaware r⫽.394, p⫽.001
Sex r⫽.488, p⬍.001
Fantastical r⫽.393, p⫽.001
Note. State daydreaming data represent only episodes when participants
reported they were daydreaming at the moment prior to being probed.
Table 12
Within- and Between Subject Predictors of end-of-Day
Creative Behavior
Predictor bp 95% CI
Level 1 predictors
Time (probe) .011 .263 [⫺.008, .031]
WS-meaning ⫺.001 .975 [⫺.082, .080]
WS-unaware .026 .514 [⫺.053, .106]
WS-planning .103 .011 [.024, .183]
WS-pleasant .003 .943 [⫺.074, .080]
WS-sex ⫺.040 .394 [⫺.133, .052]
WS-fantastical .028 .593 [⫺.074, .129]
Level 2 predictors
BS-meaning .365 .292 [⫺.314, 1.043]
BS-unaware .234 .165 [⫺.304, 1.027]
BS-planning .056 .836 [⫺.476, .589]
BS-pleasant .362 .287 [⫺.304, 1.027]
BS-sex ⫺.078 .672 [⫺.442, .285]
BS-fantastical .596 .020 [.092, 1.099]
Constant ⫺1.262 .225 [⫺3.300, .776]
Note. Data represent only episodes when participants reported they were
daydreaming at the moment prior to being probed. BS ⫽between subjects;
WS ⫽within subjects.
Table 13
Within- and Between Subject Predictors of
End-of-Day Inspiration
Predictor bp 95% CI
Level 1 predictors
Time (probe) .015 .126 [⫺.004, .034]
WS-meaning .045 .192 [⫺.023, 113]
WS-unaware .034 .310 [⫺.032, .100]
WS-planning .039 .243 [⫺.027, .106]
WS-pleasant .025 .443 [⫺.039, .089]
WS-sex ⫺.025 .536 [⫺.103, .053]
WS-fantastical .034 .439 [⫺.051, .119]
Level 2 predictors
BS-meaning .875 .008 [.203, 1.521]
BS-unaware .236 .141 [⫺.078, .550]
BS-planning ⫺.097 .708 [⫺.604, .411]
BS-pleasant .366 .257 [⫺.267, 1.00]
BS-sex ⫺.254 .152 [⫺.601, .093]
BS-fantastical .004 .986 [⫺.475, .483]
Constant ⫺1.020 .304 [⫺2.963, .923]
Note. Data represent only episodes when participants reported they were
daydreaming at the moment prior to being probed. BS ⫽between subjects;
WS ⫽within subjects.
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12 ZEDELIUS, PROTZKO, BROADWAY, AND SCHOOLER
a dynamic process that takes place only after one has reached an
impasse on a problem and has to look at information in a new way
(Baird et al., 2012), whereas daydreaming during idea generation
is counterproductive (Hao et al., 2015). Moreover, the benefits of
daydreaming might also be conditional upon problem-related
memory representations being kept active (Leszczynski et al.,
2017).
Future research might seek to explore how different types of
daydreaming immediately prior to, during, or in-between phases of
idea generation affect the idea generation process. For example,
although general tendencies for fantastical and meaningful day-
dreaming may not be associated with superior idea generation or
problem solving, engaging in fantastical daydreaming in a moment
when one is stuck might have a unique benefit. There might also
be types of daydreaming not identified here that have unique
benefits for idea generation and problem solving. Several lines of
research suggest that curious mind wandering about topics on
which one has reached an impasse may foster creative idea gen-
eration (e.g., Gable et al., 2018; Zedelius & Schooler, 2020). It
seems plausible that, whereas meaningful and fantastical mind
wandering is associated with artistic creativity, curious mind wan-
dering (i.e., mind wondering; Schooler, 2019) might enhance other
forms of creativity.
It is interesting to note that the two types of daydreaming that
emerged as the most prominent predictors of creativity seem to be
distinctive— both in content and frequency. Our data show it is not
unusual for daydreams to be highly personally meaningful. Par-
ticipants frequently reported those types of daydreams, a finding
that is congruent with previous research (Andrews-Hanna et al.,
2013). This suggests typical daydreaming is by no means a purely
trivial, dysfunctional, or disruptive activity, but part of a rich and
productive mental life that people find important. In contrast,
fantastical daydreaming is a much rarer type of daydreaming, both
according to our data and previous studies (Klinger, 2009; Kane et
al., 2017). Yet, this rare and, (according to the patterns of corre-
lations we observed) not necessarily highly meaningful or pleasant
type of daydreaming, appears to be related to artistic creativity.
This finding is in line with previous results linking fantastical
daydreaming to openness to experience and the observation that
creatively productive individuals, particularly creative writers, do
not necessarily have the most cheerful internal lives; successful
writers often suffer from stress, depression, and other mood dis-
orders (e.g., Kaufman, 2001; Ludwig, 1994). Interestingly, depres-
sion alone does not seem to benefit creative ability, but successful
writers often display a combination of stress or depression with a
rich imaginative life, perhaps indicative of a productive coping
mechanism (Kohányi, 2005; Taylor, 1999). Our results are in line
with this idea and suggest that fantastical daydreaming may play a
role in this association.
Aside from speaking to the question of how daydreaming relates
to creativity, our results also make contributions to methodological
questions. Our experience sampling results show that we gain
insights from distinguishing between trait and state conceptualiza-
tions of daydreaming. Moreover, asking participants to reflect on
their “typical” daydreaming using a self-report scale versus using
experience sampling may yield different results. We would expect
when people are asked to reflect on their “typical” daydreams, the
thoughts that come to mind may not be representative. It is
conceivable that people have superior memory for unusual or
meaningful daydreams, for instance. Interestingly, we find that, for
most daydreaming types, participants’ reports of their “typical”
(trait) daydreaming in the lab correlate moderately to highly with
their in-the-moment reports during the experience sampling pe-
riod. Planning is the only notable exception to this. Overall, this
gives us some confidence in the validity of our trait scale, but also
illustrates we cannot fully rely on the accuracy of participants’
self-reports.
There are several limitations of this study that should be con-
sidered. An important constraint is the relatively small sample size
of our main study (n⫽133), especially the experience sampling
part (n⫽65). Comparable previous experience sampling studies
have typically used larger samples (e.g., Franklin et al., 2013;
Kane et al., 2007; McVay et al., 2009). Thus, our results—
especially the experience sampling results—should be interpreted
cautiously and replicated with a larger sample. Moreover, we
observed a surprisingly high rate of daydreaming— 63%, whereas
previous studies have found much lower rates (typically around
25–35%, Franklin et al., 2013; Kane et al., 2007, 2017;
Marcusson-Clavertz et al., 2016; McVay et al., 2009; Song &
Wang, 2012; although Killingsworth & Gilbert, 2010, found a rate
of 47%). This could be due to normal sampling variation, or it
could be a methodological artifact. The notification tone we used
for thought probes was participants’ usual ring tone. Upon hearing
their phone ring, participants may have disengaged from their
current activity and started to think about who is messaging them,
for instance.
1
Using a more distinctive tone would be advisable for
future research.
Another methodological limitation is that some of the items of
our daydreaming scale, particularly Item 3 of the pleasant day-
dreaming subscale, do not load as strongly on their subscale as
expected in the confirmatory factor analyses. Negatively worded
and negatively keyed items (like Item 3) often lead to artifacts in
factor analysis of measures that are designed to be unidimensional
(e.g., Savalei & Falk, 2014; Schmitt & Stuits, 1985). We have
repeated all analyses with a modified pleasant daydreaming sub-
scale that leaves out the negatively keyed Item 3 to test if it
changes the results. It does not. Nonetheless, for future studies, the
scale should be further improved.
In conclusion, our findings show that the internal world of our
daydreams is rich and diverse, but not all daydreaming leads to
creativity. Our findings, though preliminary and in need or repli-
cation, suggest there can be at least two distinct routes between
daydreaming and creativity. One goes through personally mean-
ingful daydreams, which are surprisingly common and appear to
be a source of creative inspiration, behavior, and problem solving.
Another route goes through a much rarer, fantastical type of
daydreaming. Though seemingly frivolous, fantastical daydream-
ing may be a significant source of artistic creativity.
1
We thank Dr. Michael J. Kane for this suggestion.
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Received July 25, 2019
Revision received April 28, 2020
Accepted May 21, 2020 䡲
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