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Emotion
An Investigation of the Impact of Encounters With
Artistic Imagination on Well-Being
Peter Totterdell and Giulia Poerio
Online First Publication, June 22, 2020. http://dx.doi.org/10.1037/emo0000779
CITATION
Totterdell, P., & Poerio, G. (2020, June 22). An Investigation of the Impact of Encounters With
Artistic Imagination on Well-Being. Emotion. Advance online publication.
http://dx.doi.org/10.1037/emo0000779
An Investigation of the Impact of Encounters With Artistic Imagination
on Well-Being
Peter Totterdell
University of Sheffield
Giulia Poerio
University of Essex
Evidence about the impact of art on well-being is confined to studies of participatory arts and receptive
arts that involve attending cultural events. This investigation examined the impact of art on well-being
by framing people’s engagement with art as encounters with artistic imagination. These encounters
include traditional forms of cultural activity, such as a gallery or theater visit, but also encompass
everyday activities, such as watching a screen drama or reading fiction. Three studies examined how such
encounters affect emotional well-being, life satisfaction, meaning in life, and mental well-being. A
survey study (N⫽544) found that participants on average spent over 4 hr engaged with art the previous
day. This study and an experience-sampling study (N⫽50), in which participants completed a
questionnaire via their smartphones twice daily for 10 days (854 responses), revealed that individuals’
variety of encounters with art and accompanying elevating emotional experiences were associated with
well-being. Live arts engagement was positively associated with all aspects of well-being, and visual and
literary arts with greater meaning in life, whereas screen arts, audio arts, and sports spectating (for
comparison) were not positively associated. A third study using (live) arts attendance and well-being data
(n⫽27,918) from 2 waves (3-year interval) of a large longitudinal panel survey showed that frequency
of attendance predicted subsequent well-being, whereas arts participation did not. Overall, the evidence
indicates that encounters with artistic imagination contribute to people’s well-being, with effects varying
according to the art form and the type of well-being assessed.
Keywords: art, culture, imagination, well-being, meaning
Supplemental materials: http://dx.doi.org/10.1037/emo0000779.supp
We spend our days, each one of us, in looking for the secret of life.
Well, the secret of life is in art.
(Oscar Wilde, 1882/2016)
What did the arts ever do for us? From the perspective of the
artist, art enables expression of feelings and ideas, and from
the perspective of the audience, it provides encounters with those
feelings and ideas; but do those encounters enhance how people
feel during and about their lives? Research concerning the effects
of art on well-being has largely been confined to participatory art
activities (i.e., creating or taking part in art) and selective receptive
art activities (i.e., hearing, reading, or viewing art). In a series of
three studies, we investigate what engaging with others’ artistic
imagination and associated emotional experiences contribute to
people’s well-being.
Aesthetic Emotion and Well-Being
A pertinent way in which engaging with art might confer per-
sonal benefits for well-being is through the emotional experiences
that it provides. Mastandrea, Fagioli, and Biasi (2019) recently
proposed that aesthetic experience, which is the appreciation of
aesthetic objects, promotes health and well-being. They contend
that the psychological distancing involved in aesthetic experience
enables a pleasurable reward irrespective of the emotional valence
of the object’s content. Aesthetic experiences can arise from hu-
man objects including artworks but also from natural objects such
as forests and mountains. Pleasurable experiences arising from
time spent immersed in nature have helped explain its hedonic
impact on well-being (Capaldi, Passmore, Nisbet, Zelenski, &
Dopko, 2015).
Emotions that commonly occur in response to aesthetic objects,
including emotions such as awe and surprise, have been termed
aesthetic emotions and are differentiated by the cognitive apprais-
als that bring them about (Fayn, MacCann, Tiliopoulos, & Silvia,
2015). Awe experienced in response to nature has been shown to
explain positive changes in well-being beyond other emotions
XPeter Totterdell, Department of Psychology, University of Sheffield;
Giulia Poerio, Department of Psychology, University of Essex.
The authors declare that there is no conflict of interest with respect to the
research and its publication. This work was part of a collaborative research
partnership with Luisa Golob at Ignite Imaginations (a United Kingdom
charitable arts organization) and was funded by a research grant from Arts
Council England (32312010). We thank Elana Moore and Emily Preston-
Jones for their help with data collection in Study 2.
Correspondence concerning this article should be addressed to Peter
Totterdell, Department of Psychology, University of Sheffield, Cathedral
Court, 1 Vicar Lane, Sheffield S1 2LT, United Kingdom. E-mail:
p.totterdell@sheffield.ac.uk
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Emotion
© 2020 American Psychological Association 2020, Vol. 2, No. 999, 000
ISSN: 1528-3542 http://dx.doi.org/10.1037/emo0000779
1
(Anderson, Monroy, & Keltner, 2018). This may in part be due to
the capacity of awe to expand time perceptions thereby making life
seem less rushed (Rudd, Vohs, & Aaker, 2012). Silvia, Fayn,
Nusbaum, and Beaty (2015) characterized awe as part of a family
of elevating states involved in profound experiences and showed
that these experiences covary across nature and art domains. Ac-
cording to Huta and Ryan (2010), elevating feelings involve feel-
ing connected with a broader level of functioning and represent a
“higher range” of well-being experiences. Elevating feelings—
such as inspiration and awe— have been identified as having an
impact on eudaimonic well-being in response to an aesthetic
experience (Capaldi et al., 2015).
Accounts of personal well-being can be divided into three types
according to whether they emphasize: having pleasant experiences
in daily life (hedonic/emotional well-being), a life of meaning and
personal growth (eudaimonic well-being), or a positive cognitive
evaluation of one’s life (life satisfaction). The term subjective
well-being (SWB) has been used to refer to the combined evalu-
ations that people make of their life including their life satisfaction
and emotional well-being (i.e., having frequent or intense pleasant
feelings and infrequent or weak negative feelings; e.g., Diener,
1984). Some measures of personal well-being combine its eudai-
monic and hedonic aspects, and sometimes focus on symptoms of
social functioning or mental health (e.g., Goldberg, 1972; Tennant
et al., 2007). Concerning activities that are likely to lead to
well-being, research indicates that typically hedonic pursuits (e.g.,
activities aimed at seeking fun) relate to experiencing pleasant
affect, while eudaimonic pursuits (e.g., activities aimed at seeking
an ideal) relate to having meaning in life, and both are related to
life satisfaction (Huta & Ryan, 2010). The relative effects of
engaging with art on these three types of well-being is not yet
clear.
The Psychological Impact of Art
Much of the relevant research pertaining to the psychological
impact of art has conceptualized the arts as cultural engagement
and leisure, including activities such as visits to museums, librar-
ies, and historical sites, and leisure activities such as visiting
friends and pursuing hobbies. Psychological explanations offered
for the positive effects of cultural engagement and leisure on
physical and mental health and cognition have included: affect-
enhancement, stress-reduction, and social contact (Fancourt &
Steptoe, 2018); needs gratification, arousal, communication, and
enriched environment (Konlaan, Bygren, & Johansson, 2000);
recovery, autonomy, mastery, meaning and affiliation (Newman,
Tay, & Diener, 2014); and preparation for future events (Bygren,
Konlaan, & Johansson, 1996). In a review of arts engagement and
health-related research, Gordon-Nesbitt (2015) categorized the
principal explanations as involving effects of increased social
capital, improved cognition, protection from strain, and enriched
environment.
Relevant empirical studies have usually investigated participa-
tory art activities rather than receptive art activities or have not
distinguished between the two types. When receptive activities
have been studied, they have usually been studied as a single entity
or restricted to attendance at cultural events (e.g., theater, concert,
opera, cinema; see Fancourt & Steptoe, 2018; Gordon-Nesbitt,
2015). Studies have found positive effects of cultural engagement
on a range of outcomes, including prosociality (Van de Vyver &
Abrams, 2018), cognitive function (Fancourt & Steptoe, 2018),
self-reported health (Johansson, Konlaan, & Bygren, 2001), phys-
iology (Konlaan, Björby, et al., 2000), stress reduction (Clow &
Fredhoi, 2006), protection against obesity (Cuypers et al., 2012)
and dementia (Wang, Karp, Winblad, & Fratiglioni, 2002), cancer-
related mortality (Bygren et al., 2009), coronary-related morbidity
and mortality (Sundquist, Lindström, Malmström, Johansson, &
Sundquist, 2004), and survival (Bygren et al., 1996; Konlaan,
Bygren, et al., 2000; Väänänen et al., 2009). In relation to cultural
attendance, not all studies have found positive effects (e.g., Len-
nartsson & Silverstein, 2001) and effects can depend on the spe-
cific cultural activity involved. For example, Konlaan, Bygren, et
al. (2000) found positive effects of more frequent cinema, concert,
and art exhibition attendance on survival, but no equivalent effects
for theater attendance or reading.
Art and Well-Being
Research concerning the effects of art specifically on well-being
has mostly been confined to participatory art activities and has
often occurred in the context of health care. That research has
typically found positive changes in well-being such as reduced
stress and anxiety following a range of participatory arts interven-
tions including painting, creative writing, dance, drama, and sing-
ing (Staricoff, 2004; Stuckey & Nobel, 2010), but the quality of
studies has often been limited and effects are sometimes short-term
(e.g., Esterling, L’Abate, Murray, & Pennebaker, 1999).
We have identified four studies examining the link between
receptive arts and well-being outside of health care settings. First,
Wheatley and Bickerton (2017) examined the impact of engage-
ment in arts and sport on well-being. Using data from a large
national annual survey (Wave 2 of the “Understanding Society”
dataset) they found that attendance at arts events was positively
associated with well-being even when attendance occurred less
than once a week. Second, using the same data, Fujiwara, Kudrna,
and Dolan (2014) concluded that attendance at arts events affects
health positively but participation in arts does not. Their analysis
found that attendance at cinemas, exhibitions, plays, and music
concerts was linked with greater life satisfaction. Third, a study by
Leadbetter and O’Connor (2013) found that attendance at cultural
places and events (museums, cinema, and dance) was associated
with higher levels of life satisfaction. Fourth, a study by Cuypers
et al. (2011) of both receptive and participatory art activities found
significant associations between receptive art activities, such as
attending art exhibitions, concerts, theater, and film, and aspects of
well-being including greater life satisfaction and lower depression
and anxiety.
Longitudinal Research on the Impact of Art
The aforementioned four studies of cultural engagement and
well-being were cross-sectional in design, but longitudinal studies
of cultural engagement do exist for other types of outcome variable
(e.g., prosociality—Van de Vyver & Abrams, 2018). Gordon-
Nesbitt (2015) identified 14 studies stemming from Scandinavia
that demonstrate the longitudinal impact of cultural participation
and cultural attendance on health outcomes (including some psy-
chological outcomes) in nonclinical settings over long periods of
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2TOTTERDELL AND POERIO
time (i.e., years). However, none of these studies examined within-
person associations between cultural engagement and outcomes
over time. Such an approach would enable comparisons between
occasions (e.g., occasions with no engagement vs. occasions with
engagement) rather than comparisons between individuals that
may be confounded by individual and demographic differences
(see Gordon-Nesbitt, 2015, p. 55).
Current Research Investigation
The current investigation offers an alternative to predominant
cultural perspectives on art that have focused on its intrinsic and
instrumental merits (e.g., Vuyk, 2010). Instead we have sought to
understand and assess the prevalence and psychological value of
the arts to well-being in everyday life by conceptualizing receptive
arts activity as encounters with artistic imagination. This concep-
tion encompasses the full range of possible art forms (visual,
literary, audio, screen, performance/live) and includes what might
be deemed “low art” (e.g., soap opera) as well as “high art” (e.g.,
opera), and on-demand art (e.g., music streaming) as well as event
art (e.g., art exhibition). In alignment with scholars who have
identified aesthetic experience as central to the contribution of art
to well-being, we have examined how people’s emotional re-
sponses to encounters with artistic imagination contributes to their
well-being by studying their elevating feelings.
We conducted three studies to elucidate the variety, duration,
and emotional impact of people’s everyday encounters with artistic
imagination, and their effects on well-being. The three studies used
different research methods and different timescales. Study 1 was a
survey of 500⫹adults that examined their encounters with artistic
imagination and well-being across the course of one day. This
research design was used to test associations between encounters
with art and well-being based on between-person comparisons.
Study 2 was an experience-sampling study of 50 adults who
reported their encounters with artistic imagination and their well-
being twice a day for 10 days. This research design was used to test
associations between encounters with arts and well-being based on
within-person comparisons (i.e., how well-being varied in relation
to arts engagement from half day to half day). Study 3 was a
longitudinal survey of 27,000⫹adults that tested whether their
annual frequency of attendance at live arts events was associated
with their well-being 3 years later. The size of this dataset enabled
inclusion of a large set of control variables. We included several
other features in the design of the studies that add value to extant
research: the diversity of receptive arts studied, the inclusion of
people’s emotional response to their encounters with art, the range
of well-being measures used, and the inclusion of benchmark
activities for comparison.
Diversity of Receptive Arts
Studies of cultural engagement involving the receptive arts have
mostly looked at events that are attended (i.e., performance/live
arts). Some studies have included other types of activity (such as
reading or watching TV) but the nature of these activities is rarely
specified (e.g., whether they involved imagined worlds or real
events) and the range of activity studied is usually quite restricted.
In Studies 1 and 2, we have included a wide range of receptive arts
activities that span visual, live, audio, screen, and literary arts, and
have looked at the separate effects of these categories.
Emotional Response to Art
Our studies examined the effects of variety and duration of
encounters with art on well-being. However, according to Wheat-
ley and Bickerton (2017), it may be the quality rather than the
quantity of cultural experiences that is crucial to deriving positive
experiences and obtaining effects on well-being. In line with this
view, Djikic and Oatley (2014) proposed that individuals who
resonate more strongly with art, as indicated by strong emotions,
are more likely to incorporate other people’s experience into their
own and thereby produce changes to themselves. Consequently, in
Studies 1 and 2, we examined the effect of elevating experiences
(Huta & Ryan, 2010) in response to encounters with art, as well as
looking at the effects of variety and duration on well-being.
Types of Well-Being
When people appreciate art it can contribute to their well-being
in a fashion that is not just hedonistic (Oliver & Bartsch, 2010) but
also extends to meaningfulness (e.g., Oliver & Raney, 2011). Yet
the contribution of different categories of receptive art activities to
different types of well-being is unknown. We therefore included
measures of emotional well-being, life satisfaction, and eudai-
monic well-being (meaning in life) in Studies 1 and 2 to examine
these different relations.
Benchmark Activities
Some studies of cultural engagement have included alternative
activities against which the effects of cultural activity could be
compared. Sports attendance (Konlaan, Bygren, et al., 2000) and
sports participation (Van de Vyver & Abrams, 2018; Wheatley &
Bickerton, 2017) have both been used for this purpose. Sports
attendance provides a good comparison activity for encounters
with art because both entail participants being an audience to the
activity. We therefore included sports attendance in Studies 1 and
2 but extended its reach to include all forms of sports spectating to
make it comparable to a wider range of receptive arts (not just live
events). For Study 3, we switched to using frequency of partici-
pation in sports as our comparison activity because taking part in
exercise is firmly established as having positive associations with
well-being (e.g., Downward & Rasciute, 2011).
Study 1
Method
Participants. A total of 544 participants took part in the study
(M
age
⫽32.45 years, SD ⫽12.93, Range: 18 –75). Of the sample,
70% were female and 29% were male; the remainder of the sample
did not identify with either gender or opted not to say. The
majority of the sample consisted of students (40%) and full-time
workers (36%), but also included part-time workers (11%), those
who are self-employed (4%), retired (3%), employed casually/
occasionally (2%), unemployed (2%), volunteers (1%), and home-
makers (1%). Nearly all participants (97%) reported currently
living in the United Kingdom for most of the time. Fifty-three
percent of the sample reported a household income below the U.K.
median (less than GBP 35,200), 37% reported a household income
above the U.K. median and the remainder of the sample opted not
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3
ENCOUNTERS WITH ART AND WELL-BEING
to answer. Participants were invited to take part in the online
survey though a variety of means including a University staff and
student mailing list, via social media (Twitter, Facebook), and
leafleting at a sporting event. The study was described as an
investigation into how people engage with the arts in daily life and
how arts engagement is related to well-being and personality.
Participants who completed the survey were entered in a prize
draw to win a GBP 50 Amazon voucher. Ethics approval was
obtained from the host university.
Measures.
Encounters with the arts.
Type of arts activity and duration. Participants were asked to
think back to the previous day and consider “how you experienced
and engaged with the arts such as through TV, radio, online (e.g.,
websites), or by attending various events.” The previous day for
the majority (51%) of responses was Thursday. Fifteen percent of
the responses were answered about Sunday, 10% about Monday,
7% about Tuesday, 7% about Saturday, 5% about Friday, and 5%
about Wednesday. Participants selected all the arts activities that
they had engaged with the previous day from a list of 10 activity
groups which were later assembled into five broader arts catego-
ries as follows: (a) Visual arts (two activity groups): drawings/
paintings/photography/video art, ceramics/sculpture/conceptual
art, (b) Live arts (three activity groups): live music, dance, theater
(including opera, stand-up, verse), (c) Literary arts (two activity
groups): book (fiction)/novel/story/comic, poetry, (d) Screen arts
(two activity groups): film/movie, drama (including soaps and
sitcoms), and (e) Audio arts (one activity group): recorded music.
For comparative purposes, participants also indicated whether they
watched, listened to or attended any sports activities the previous
day. Participants recorded the amount of time they had spent on
each activity the previous day to the nearest quarter of an hour.
Elevating experience of arts activity. Participants were asked
to think about how the content of one of the activities—randomly
selected from those that they had indicated they had engaged with
the previous day (including sport)— had made them feel. They
responded using the eight-item elevating experience scale (Huta &
Ryan, 2010, Study 2). Elevating experience was a term used by
Huta and Ryan (2010) to describe the “higher” range of well-being
experiences that involve connection with and elevation to a
broader level of functioning. The scale, which has been associated
with eudaimonic pursuits, encompasses experiences of Inspiration
(inspired, enriched, morally elevated), Awe (in awe, deeply ap-
preciating, emotionally moved) and Transcendence or sense of
connection with a greater whole (connected with a greater whole,
part of something greater than yourself). Responses were made on
a 5-point scale from 1 (not at all)to5(a great deal). Items were
averaged such that higher scores represented greater elevating
experience during the activity (␣⫽.91).
Well-being. After reporting on their arts encounters the pre-
vious day, participants rated various aspects of their well-being
with reference to the previous day. When rating their well-being,
participants were instructed to think back to everything that hap-
pened the previous day and consider the day as a whole. The scales
were presented in a random order and the items in each scale were
also individually randomized.
Emotional well-being. Emotional well-being was measured
using the Multi-Affect Indicator (Warr, Bindl, Parker, & Inceoglu,
2014), which provides an index of both valence and arousal
dimensions of core affect (Remington, Fabrigar, & Visser, 2000).
Each of four subscales were measured using three items: (a) high
activation pleasant affect (enthusiastic, joyful, excited), (b) low
activation pleasant affect (at ease, calm, laid back), (c) high acti-
vation unpleasant affect (anxious, tense, worried), and (d) low
activation unpleasant affect (dejected, depressed, hopeless). Par-
ticipants rated the extent to which they felt each of the feelings
described the previous day on a 5-point scale from 1 (not at all)to
5(a great deal). The subscales for unpleasant affect were reverse
scored and an overall score for emotional well-being was created
from the mean of the four subscales (␣⫽.81).
Life satisfaction. Life satisfaction was measured using the
5-item Satisfaction with Life Scale (Diener, Emmons, Larsen, &
Griffin, 1985) which was adapted to refer to the previous day (e.g.,
“I was satisfied with my life yesterday,”, “In most ways yesterday
was close to my ideal”). Participants rated their agreement with
each item on a 7-point scale from 1 (strongly disagree)to7
(strongly agree). Items were summed to provide an overall score
where higher values indicate greater satisfaction with life the
previous day (␣⫽.88).
Meaning in life. Presence of meaning in life the previous day
was measured using two items adapted from the Meaning in Life
Scale (Steger, Frazier, Oishi, & Kaler, 2006). Participants rated
their agreement to the two items (“Yesterday my life felt mean-
ingful,” “Yesterday I felt like my life had purpose”) on a 7-point
scale from 1 (strongly disagree)to7(strongly agree). Items were
averaged to provide an overall score where higher values indicate
greater presence of meaning in life the previous day (␣⫽.85).
Mental well-being. The 14-item Warwick-Edinburgh Mental
Well-Being Scale (WEMWBS; Tennant et al., 2007) was used to
provide an overall indication of general mental well-being. The
scale was designed to capture both hedonic and eudaimonic as-
pects of well-being including affective-emotional aspects,
cognitive-evaluative dimensions, and psychological and social
functioning. Participants read each of the statements about feelings
and thoughts and chose the response that best described their
experience over the previous day on a 5-point scale from 1 (none
of the time)to5(all of the time). Example items included: “I felt
optimistic about the future,” “I felt close to other people,” and “I
was interested in new things.” Items were summed to provide an
overall score where higher values indicated greater mental well-
being the previous day (␣⫽.92).
Results
Arts activities. Table 1 shows the variety and duration of the
participants’ encounters with the five broader arts categories. On
average, participants engaged with 2.60 (SD ⫽1.11, Range: 1– 6)
arts activities and spent 4.21 hr engaging with the arts the previous
day. Of the arts categories, screen arts were engaged with most
frequently, followed by audio arts, literary arts, visual arts, and live
arts. Eighteen participants (3.3%) had no engagement with arts
activities the previous day. Participants engaged with sports more
frequently than live arts but less frequently than any other arts
category. On average, participants spent the most time engaged in
screen and audio arts, followed by literary, visual and live arts.
Participants spent less time engaged with sports compared to all
the arts categories.
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4TOTTERDELL AND POERIO
Arts encounters and well-being. To examine the potential
impact of the arts on well-being we ran a series of regression
models for each well-being variable. We examined the following
as predictors of well-being: (a) the variety of arts activities en-
gaged with (i.e., the number of different activities), (b) the total
time spent engaged with the arts, and (c) the time spent in each of
the arts categories. In all analyses age and income (0 ⫽less than
35, 200 and 1 ⫽more than 35, 200; split based on median U.K.
household income GBP) were entered as control variables. Income
was measured dichotomously because of its personally sensitive
nature. Of the demographic and weekday variables tested, only age
and income showed consistent relationships with the well-being
variables (a minimum of two significant correlations). They also
have potential to influence people’s opportunity and preference for
engaging with different arts so may confound any apparent rela-
tionship between art activity and well-being. A sensitivity analysis
indicated that regression models with eight predictors including
these control variables would be able to detect a small effect (f
2
⫽
.03) with power ⫽0.80 at ␣⫽.05 for N⫽544.
Do variety of engagement and total time spent engaged with
arts activities predict well-being? Regression models for the
four well-being variables showed that variety of arts activities was
a positive predictor of life satisfaction (B⫽0.63, SE ⫽0.27, ⫽
0.11, t⫽2.30, p⫽.022, 95% CI [0.09, 1.17]) and meaning in life
(B⫽0.12, SE ⫽0.06, ⫽0.10, t⫽2.13, p⫽.034, 95% CI [0.01,
0.23]), suggesting that people who had engaged in a greater variety
of arts activities also reported greater life satisfaction and meaning
in life for that day (see Table 2). In contrast, total time spent
engaged with arts activities (when used instead of the variety
variable) was not a significant predictor of any aspect of well-
being for that day.
Does time engaged in each arts category and sports spectating
predict well-being? A multivariate general linear model with the
five arts categories and sport as predictors (see Table S1 in the
online supplementary materials) showed significant multivariate
effects on well-being for live arts, F(4, 432) ⫽3.77, p⫽.005,
p
2⫽.03 and screen arts, F(4, 432) ⫽2.68, p⫽.031, p
2⫽.02.
More time engaged with live arts predicted higher levels of emo-
tional well-being (B⫽0.11, SE ⫽0.04, p
2⫽0.02, t⫽2.91, p⫽
.004, 95% CI [0.03, 0.18]), higher levels of life satisfaction (B⫽
1.22, SE ⫽0.34, p
2⫽0.03, t⫽3.57, p⬍.001, 95% CI [0.55,
1.89]), higher levels of meaning in life (B⫽0.15, SE ⫽0.07,
p
2⫽0.01, t⫽2.18, p⫽.030, 95% CI [0.02, 0.29]), and higher
levels of mental well-being (B⫽1.40, SE ⫽0.70, p
2⫽0.01,
t⫽2.01, p⫽.045, 95% CI [0.03, 2.77]). In contrast, more time
engaged with screen arts predicted lower levels of meaning in
life (B⫽⫺0.10, SE ⫽0.05, p
2⫽0.01, t⫽⫺2.23, p⫽.026,
95% CI [⫺0.20, ⫺0.01]). Time engaged with sport was not a
significant predictor of any of the well-being variables.
Elevating experience.
Does elevating experience during arts engagement predict
well-being? Elevating experience (in response to the randomly
chosen art activity) was a significant positive predictor of all the
well-being variables: emotional well-being (B⫽0.08, SE ⫽0.04,
⫽0.10, t⫽2.20, p⫽.029, 95% CI [0.01, 0.16]), life satisfac-
tion (B⫽1.50, SE ⫽0.36, ⫽0.20, t⫽4.21, p⬍.001, 95% CI
[0.80, 2.19]), meaning in life (B⫽0.37, SE ⫽0.07, ⫽0.23, t⫽
5.10, p⬍.001, 95% CI [0.23, 0.51]), and mental well-being (B⫽
Table 1
Descriptive Statistics for Art/Sport Activities and Elevating Experiences in Study 1 (N ⫽544) and Study 2 (N ⫽50; 854 Occasions)
Category of
activity
Study 1 Study 1 Study 1 Study 2 Study 2 Study 2
Incidence
n
Duration
M(SD) hr.
Elevating experience
M(SE) 1–5
Duration per half day
M(SD) hr.
Duration per half day
M(SD) hr.
Elevating experience
M(SE) 1–7
Screen arts 398 1.40 (1.52) 2.55 (.07) 1.53 (.60) 0.49 (.36) 4.15 (.11)
Audio arts 374 1.48 (1.75) 2.86 (.08) 1.14 (.58) 0.33 (.31) 4.25 (.12)
Literary arts 298 0.70 (1.07) 3.11 (.08) 0.88 (.51) 0.14 (.22) 4.62 (.14)
Visual arts 195 0.34 (0.74) 3.12 (.12) 0.94 (.67) 0.13 (.20) 4.49 (.14)
Live arts 83 0.29 (0.94) 3.33 (.17) 1.56 (.82) 0.09 (.15) 5.01 (.18)
Sports 89 0.20 (0.56) 2.66 (.14) 0.93 (.42) 0.16 (.26) —
All arts — 4.21 (2.74) — 1.82 (.70) (excludes zero engagement) 1.17 (.56) (includes zero engagement) —
Note. Sports refers to spectating (not partaking). Means for elevating experience in Study 2 are multilevel model estimates.
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5
ENCOUNTERS WITH ART AND WELL-BEING
2.94, SE ⫽0.71, ⫽0.19, t⫽4.13, p⬍.001, 95% CI [1.54,
4.34]; see Table 2).
Are different arts categories associated with greater levels of
elevating experience compared to sports spectating? To test this
question, we conducted a one-way ANOVA with activity category
(visual, literary, live, screen, audio, sports) as the independent
variable and elevating experience as the dependent variable. Mean
levels of elevating experience for each arts category are presented
in Table 1. There was a significant main effect of activity category,
F(5, 501) ⫽8.10, p⬍.001, p
2⫽.08. Pairwise comparisons to
examine differences in elevating experience between the art cate-
gories and sport showed that, on average, visual arts (M
diff
⫽0.46,
SE ⫽0.18, p⫽.011, 95% CI [0.11, 0.81]), live arts (M
diff
⫽0.67,
SE ⫽0.22, p⫽.002, 95% CI [0.24, 1.10]), and literary arts
(M
diff
⫽0.45, SE ⫽0.16, p⫽.006, 95% CI [0.13, 0.77]) were
associated with higher levels of elevating experience. Levels of
elevating experience did not differ between screen arts and sports
(M
diff
⫽⫺0.11, SE ⫽0.16, p⫽.487, 95% CI [⫺0.42, 0.20]) or
between audio arts and sport (M
diff
⫽0.20, SE ⫽0.16, p⫽.198,
95% CI [⫺0.11, 0.52]).
We also examined whether levels of elevating experience dif-
fered between the arts categories. Live arts were associated with
significantly higher levels of elevating experience compared to
both screen (M
diff
⫽0.78, SE ⫽0.18, p⬍.001, 95% CI [0.42,
1.14]) and audio arts (M
diff
⫽0.46, SE ⫽0.19, p⫽.013, 95% CI
[0.10, 0.83]). Literary arts were also associated with significantly
higher levels of elevating experience compared to both screen
(M
diff
⫽0.56, SE ⫽0.11, p⬍.001, 95% CI [0.33, 0.78]) and audio
arts (M
diff
⫽0.24, SE ⫽0.12, p⫽.040, 95% CI [0.01, 0.47]).
Visual arts were associated with significantly higher levels of
elevating experience compared to screen (but not audio) arts
(M
diff
⫽0.57, SE ⫽0.14, p⬍.001, 95% CI [0.30, 0.83]). Audio
art was associated with significantly higher levels of elevating
experience compared to screen arts (M
diff
⫽0.31, SE ⫽0.11, p⫽
.004, 95% CI [0.10, 0.53]).
Summary of findings. The results suggest that people spend
a substantial amount of time (over 4 hr) each day engaging with
the artistic imagination of others, and only a minority of people
(about 3%) had no such encounters. Spending more of the day
engaged with art was not associated with well-being, whereas
engaging with more kinds of art was associated with greater
satisfaction and meaning in life. Experiencing greater elevating
feelings in response to art was positively associated with all forms
of well-being. With respect to different categories of art, live arts
Table 2
Multiple Regression Analysis Testing the Predictive Effect of (A) Variety of Arts Engaged With
and (B) Elevating Experience in Response to Art, on Well-Being in Study 1 (N ⫽544)
Variables in models BSEtpCI-L CI-U
(A)
Emotional well-being R
2
⫽.01, F(3, 450) ⫽2.09, p⫽.100
Age ⫺0.01 0.01 ⫺0.01 ⫺0.23 .815 [⫺0.01, 0.01]
Income 0.16 0.07 0.11 2.29 .022 [0.02, 0.30]
Variety of arts 0.03 0.03 0.05 1.12 .262 [⫺0.02, 0.09]
Life satisfaction R
2
⫽.02, F(3, 450) ⫽3.29, p⫽.021
Age ⬍.01 0.03 ⬍.01 0.02 .983 [⫺0.05, 0.05]
Income 1.47 0.67 0.10 2.18 .030 [0.14, 2.79]
Variety of arts 0.63 0.27 0.11 2.30 .022 [0.09, 1.17]
Meaning in life R
2
⫽.05, F(3, 449) ⫽7.14, p⬍.001
Age 0.01 0.01 0.12 2.61 .009 [0.00, 0.02]
Income 0.36 0.14 0.12 2.63 .009 [0.09, 0.64]
Variety of arts 0.12 0.06 0.10 2.13 .034 [0.01, 0.23]
Mental well-being R
2
⫽.02, F(3, 452) ⫽3.29, p⫽.021
Age 0.10 0.05 0.09 1.90 .058 [0.00, 0.20]
Income 2.21 1.36 0.08 1.63 .104 [⫺0.46, 4.89]
Variety of arts 0.81 0.55 0.07 1.48 .141 [⫺0.27, 1.90]
(B)
Emotional well-being R
2
⫽.02, F(3, 435) ⫽3.18, p⫽.024
Age ⫺0.01 0.01 ⫺0.02 ⫺0.35 .728 [⫺0.01, 0.01]
Income 0.15 0.07 0.10 2.14 .033 [0.01, 0.29]
Elevating experience 0.08 0.04 0.10 2.20 .029 [0.01, 0.16]
Life satisfaction R
2
⫽.05, F(3, 432) ⫽7.33, p⬍.001
Age ⫺0.01 0.03 ⫺0.01 ⫺0.05 .962 [⫺0.05, 0.05]
Income 1.34 0.68 0.10 1.98 .049 [0.01, 2.67]
Elevating experience 1.50 0.36 0.20 4.21 ⬍.001 [0.80, 2.19]
Meaning in life R
2
⫽.09, F(3, 432) ⫽14.09, p⬍.001
Age 0.02 0.01 0.13 2.79 .005 [0.01, 0.03]
Income 0.32 0.14 0.11 2.34 .020 [0.05, 0.59]
Elevating experience 0.37 0.07 0.23 5.10 ⬍.001 [0.23, 0.51]
Mental well-being R
2
⫽.05, F(3, 435) ⫽8.22, p⬍.001
Age 0.11 0.05 0.10 2.11 .036 [0.01 0.21]
Income 1.77 1.35 0.06 1.30 .193 [⫺0.90, 4.43]
Elevating experience 2.94 0.71 0.19 4.13 ⬍.001 [1.54, 4.34]
Note. 95% confidence interval: Lower (CI-L), Upper (CI-U) bounds. Coding: Income (household)— below UK
median (0), above UK median (1).
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6TOTTERDELL AND POERIO
and visual arts produced the strongest elevating experiences and
spending more time on them had positive associations with well-
being (unlike sports spectating); yet they were less frequently
engaged with than audio and screen arts, even though these had a
null or negative association with well-being.
Study 2
Study 1 examined whether individuals who engaged more with
art on a single day experienced higher levels of well-being than
those who engaged less. The purpose of Study 2 was to use an
experience-sampling method to examine whether individuals ex-
perience higher levels of well-being on occasions when they
engage more with art compared to occasions when they engage
less. Use of an experience-sampling method also made it feasible
to examine how often individuals engage with art, differences in
well-being between occasions when they do and do not engage
with art, and whether well-being also acts as a precursor of arts
engagement. Another advantage of the method was that it relied
less on individuals’ ability to accurately recall and aggregate past
events than Study 1.
Method
Participants. Fifty participants took part in the study (M
age
⫽
36.80 years, SD ⫽11.75, Range: 20 – 69), which was described to
them as an exploration of arts engagement and well-being in daily
life. The study was advertised on social media, through mailing
lists and by word of mouth. Participants were provided with a GBP
10 high-street voucher in exchange for their participation. Of the
sample, 39 participants (78%) were female. In terms of ethnicity,
88% of the sample were White, 10% came from a mixed/multiple
ethnic background, and 2% were Asian/Asian British. The sample
mainly consisted of full-time workers (28%), part-time workers
(20%), and students (28%) but also included those who are retired
(8%), self-employed (6%), employed occasionally/causally (4%),
unemployed (4%), and volunteers (1%). Fifty-eight percent of the
sample reported a household income of less than GBP 35, 200
(U.K. household median), 18% reported a household income
above GBP 35, 200 and the remainder of the sample opted not to
disclose this information. Ethics approval was obtained from the
host university.
Experience-sampling protocol. Participants’ encounters with
the arts and their momentary well-being were sampled twice daily
for 10 days. The selection and balance of sample size and number
of sampling points was based on recommendations by Kreft and de
Leeuw (1998) for testing multilevel models. Both elements con-
tribute to power but sample size makes the greater contribution.
The study was administered using participants’ own smartphones
in conjunction with SurveySignal software (Hofmann & Patel,
2015).
1
Participants received each signal as a text message with a
link to an online survey created in Qualtrics. Signals occurred at
the same time each day and participants chose whether to receive
the signals at either 13:00 and 21:00, 14:00 and 22:00, or 15:00
and 23:00, depending on their waking hours. Signals were timed so
that each response about arts engagement covered approximately a
half-day period. Reminder surveys were sent after 30 min if
participants had not responded and participants were given 3 hr to
answer the survey before the link expired (meaning that they were
no longer able to provide a response). Participants started the study
on either a Thursday or Friday so that the sampling period spanned
two weekends. Participants individually provided M⫽17.08
(SD ⫽2.64) responses (of maximum 20) and together completed
854 out of a possible 1,000 responses corresponding to an 85%
response rate. Compliance at each response point was M⫽42.70
(SD ⫽12.43; of maximum 50).
Measures.
Encountered art: Type and duration. Participants selected all
the art forms they had encountered so far that day or since their last
signal (for the first and second text message of each day respec-
tively). If they missed the first signal they were asked to reflect on
their encounters with art in the period from the first signal (e.g.,
13:00) to when answering the survey. Participants selected which
art forms they had encountered from the same activities and
categories (visual, live, literary, screen, audio) as Study 1. Partic-
ipants recorded the amount of time they had engaged with each
activity over the last half day (to the nearest quarter of an hour).
Engagement with sport. For comparative purposes partici-
pants also indicated how long they had watched, listened to or
attended any sports activities during the sampling period.
Most recent arts encounter. Participants selected the encoun-
ter with art that occurred most recently. If the time they had spent
engaged with that most recent activity was different from the
duration estimate given previously (because they had engaged with
that activity more than once in the half day) then participants
recorded how long the most recent encounter had lasted. Partici-
pants also indicated approximately how long ago that activity
occurred (if we interrupted them during the activity they would
indicate this by specifying 0 hr 0 min) and whether they had
engaged with that arts activity alone or with other people. If
participants had previously indicated that they had not encountered
any art forms during the last half day, the survey skipped to
questions about their current well-being.
Elevating experience of most recent arts encounter. With
reference to their most recent encounter with art, participants rated
six items from the elevating experience scale (Huta & Ryan, 2010,
Study 2): inspired, enriched, deeply appreciating, emotionally
moved, connected with a greater whole, part of something greater
than yourself. Ratings were made on a 7-point scale from 1
(strongly disagree)to7(strongly agree) and were averaged to
create an overall score such that higher values indicated greater
elevating experience during the most recent arts activity (within-
person reliability ⫽.80; see Shrout & Lane, 2012).
Current well-being. Participants rated how they felt in the
moments before answering the survey. All items were answered on
a 7-point scale from 1 (not at all)to7(extremely). Items were
individually randomized for each presentation.
Emotional well-being. Participants rated four items concern-
ing their feelings in the moment taken from the Multi-Affect
Indicator (Warr et al., 2014) to measure high-activation and low-
activation pleasant affect and high-activation and low-activation
unpleasant affect (enthusiastic, calm, tense, depressed). The two
negative emotion items were reversed scored and combined with
the two positive emotion items to create an average score for
1
Participants could borrow a smartphone from the researchers if they
did not own one, but one participant preferred to receive signals via e-mail.
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7
ENCOUNTERS WITH ART AND WELL-BEING
emotional well-being such that higher scores indicated greater
emotional well-being (within-person reliability ⫽0.51).
Life satisfaction. Participants rated a single item: “Satisfied
with your life” concerning their feelings in the moment adapted
from the Satisfaction with Life Scale (Diener et al., 1985).
Meaning in life. Participants rated two items “That your life
has purpose,” “That your life feels meaningful” concerning their
feelings in the moment adapted from the Meaning in Life Scale
(Steger et al., 2006). Items were averaged to provide an overall
score where higher values indicate greater presence of meaning in
life (within-person reliability ⫽.65).
Procedure. Participants attended a training session where
they were given written and verbal instructions for the study. They
were told that the study sought to understand how people engaged
with the arts in their daily lives and how this might relate to
well-being. A broad definition of the arts was included to capture
encounters with artistic imagination, and participants were told to
exclude any personal involvement in creating art (participatory art)
in their answers. The researcher explained the meaning and re-
sponse to each item in the experience-sampling questionnaire and
provided a demonstration of the signaling method. Participants
were provided with the researcher’s contact details in case they
had any problems with the study or signaling method and the
researcher contacted the participant after 3– 4 days of the
experience-sampling period to check on progress.
Analysis overview. Most analyses were conducted using the
mixed procedure in IBM SPSS due to the nested structure of our
data (e.g., arts encounters and well-being [Level 1] nested within
individuals [Level 2]). Continuous Level 1 predictor variables
were group-mean centered (and associated models also included
the subtracted group mean as a variable; Kreft & de Leeuw, 1998);
continuous Level 2 predictors (i.e., age) were grand-mean cen-
tered. As per Study 1, all models included age and income as
predictor variables. Intercepts but not slopes were allowed to vary
and the nonindependence of observations within individuals was
modeled by fitting an autoregressive correlation structure to the
Level 1 residuals. For multilevel models with binary outcomes we
used generalized estimation equations (GEE; Liang & Zeger,
1986).
Results
Descriptive statistics. Data for time spent in each activity
category were aggregated to Level 2. We calculated two types of
aggregate scores. The first type reflected the average time spent by
participants per sampling point (i.e., every half day) in each arts
category and overall, when they had engaged with arts activities.
This data did not include the 280 occasions (32.8%) when there
was no engagement with an arts activity (i.e., 0 hr) and so reflected
the time that participants typically spent engaged with an arts
activity when it was encountered. The second type reflected the
average time spent by participants per sampling point (i.e., every
half day) in each arts category and overall, including time when
they had not engaged with arts activities. Descriptive statistics for
time spent in each art category are presented in Table 1. Depending
on the type of score used, the results indicate that participants on
average spent 3.64 or 2.34 hr a day engaged with arts. Data from
the participants’ most recent arts activity showed that they engaged
with the activity with other people on 48.1% occasions, but this
varied depending on the category (live arts 82.9%, screen arts
65.5%, visual arts 45.5%, audio arts 38.9%, literary arts 8.3%).
Arts encounters and momentary well-being. To examine
the potential impact of the arts on momentary well-being we ran a
series of multilevel regression models for each type of well-being
(emotional well-being, life satisfaction, and meaning in life). We
examined the following as predictors of well-being: (a) the total
time spent engaged with arts, (b) engaging versus not engaging
with arts (coded 1, 0, respectively), and (c) engaging versus not
engaging with each arts category (also coded 1, 0). For compari-
son, duration and engagement with sports were included as pre-
dictor variables in the models involving time and engagement
respectively.
Does total time spent engaged with arts predict momentary
well-being? The total time people spent engaged with arts in the
past half day positively predicted all aspects of their well-being:
emotional well-being: (⫽0.08, SE ⫽0.02, t(658) ⫽3.71, p⬍
.001, 95% CI [0.04, 0.13]), life satisfaction: (⫽0.09, SE ⫽.02,
t(685) ⫽3.77, p⬍.001, 95% CI [0.04, 0.14]), and meaning in life:
(⫽0.05, SE ⫽0.02, t(710) ⫽2.68, p⫽.008, 95% CI [0.01,
0.09]). Time spent engaged with sport did not predict any aspect of
well-being. See Table S2 in the online supplementary materials.
Does engaging with arts (vs. not engaging) predict momentary
well-being? Engaging with arts was a significant predictor of
greater emotional well-being (⫽0.23, SE ⫽0.07, t(687) ⫽3.45,
p⫽.001, 95% CI [0.10, 0.36]) and meaning in life (⫽0.13,
SE ⫽.06, t(724) ⫽2.26, p⫽.024, 95% CI [0.02, 0.24]) and was
a marginal predictor of greater life satisfaction (⫽0.13, SE ⫽
0.07, t(708) ⫽1.77, p⫽.077, 95% CI [⫺0.10, 0.28]). In contrast,
engaging with sports was not a significant predictor of any of the
well-being variables. See Table S2 in the online supplementary
materials.
Does engaging (vs. not engaging) with each arts category
predict momentary well-being? Fixed effects from the relevant
multilevel models for the three well-being variables (see Table 3)
showed that engagement with live arts was a significant positive
predictor of all aspects of well-being: emotional well-being (⫽
0.47, SE ⫽0.13, t(656) ⫽3.58, p⬍.001, 95% CI [0.21, 0.74]),
life satisfaction (⫽0.30, SE ⫽0.15, t(679) ⫽2.07, p⫽.038,
95% CI [0.02, 0.59]), and meaning in life (⫽0.25, SE ⫽0.11,
t(698) ⫽2.17, p⫽.030, 95% CI [0.02, 0.47]). Engaging with
visual arts (⫽0.18, SE ⫽0.09, t(765) ⫽2.05, p⫽.041, 95% CI
[0.01, 0.35]) and literary arts (⫽0.16, SE ⫽0.08, t(756) ⫽1.96,
p⫽.050, 95% CI [0.00, 0.31]) were significant positive predictors
of meaning in life. Engagement with audio arts and screen arts did
not predict any of the well-being measures.
Elevating experience.
Does elevating experience during arts engagement predict
well-being? Elevating experience (in response to participants’
most recent arts activity) was a significant positive predictor of all
aspects of well-being (see Table S2 in the online supplementary
materials): emotional well-being (⫽0.16, SE ⫽0.04, t(468) ⫽
3.85, p⬍.001, 95% CI [0.08, 0.23]), life satisfaction (⫽0.17,
SE ⫽0.04, t(478) ⫽4.02, p⬍.001, 95% CI [0.09, 0.25]), and
meaning in life (⫽0.21, SE ⫽0.03, t(484) ⫽6.39, p⬍.001,
95% CI [0.14, ⫺0.27]).
Are some arts categories associated with greater levels of
elevating experience? To test this question, we used a multilevel
regression model with participants’ most recent arts category as a
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8TOTTERDELL AND POERIO
predictor of elevating experience. Descriptive statistics for each
arts category are provided in Table 1. Overall, engaging with an
arts category had a significant effect on elevating experience, F(4,
485) ⫽8.76, p⬍.001. Specifically, engaging with live arts (⫽
0.86, SE ⫽0.17, t(488) ⫽4.96, p⬍.001, 95% CI [0.52, 1.20]),
visual arts (⫽0.34, SE ⫽0.13, t(482) ⫽2.58, p⫽.010, 95% CI
[0.08, 0.60]), and literary arts (⫽0.47, SE ⫽0.13, t(484) ⫽3.71,
p⬍.001, 95% CI [0.22, 0.72]) were significantly associated with
greater levels of elevating experience than engaging with screen
arts (reference category), but audio arts was not (⫽0.11, SE ⫽
0.11, t(480) ⫽1.01, p⫽.314, 95% CI [⫺.10, 0.32]).
Does engaging with arts with other people (vs. alone) predict
momentary well-being and elevating experience? The presence
of other people during participants’ most recent arts activity was a
significant positive predictor of emotional well-being (⫽0.22,
SE ⫽0.08, t(486) ⫽2.79, p⫽.006, 95% CI [0.06, 0.37]) and life
satisfaction (⫽0.29, SE ⫽0.08, t(489) ⫽3.47, p⫽.001, 95%
CI [0.13, 0.45]), but not meaning in life (⫽0.10, SE ⫽0.07,
t(489) ⫽1.57, p⫽.117, 95% CI [⫺0.03, 0.23]) or elevating
experience (⫽0.11, SE ⫽0.09, t(524) ⫽1.22, p⫽.224, 95%
CI [⫺0.06, 0.28]).
The effect of prior well-being on arts engagement. To ex-
amine whether prior well-being predicted engagement with arts we
first ran a multilevel regression model with the (first-order) lags of
the well-being variables as predictors of total time in arts engage-
ment. The lags of the well-being variables did not significantly
predict total time engaged in arts activities: lag of emotional
well-being (⫽⫺0.02, SE ⫽0.02, t(173) ⫽⫺1.00, p⫽.321,
95% CI [⫺0.07, 0.02]), lag of life satisfaction (⫽⫺0.03, SE ⫽
0.03, t(162) ⫽⫺1.06, p⫽.290, 95% CI [⫺0.08, 0.02]), and lag
of meaning in life (⫽0.03, SE ⫽0.03, t(169) ⫽1.02, p⫽.309,
95% CI [⫺0.03, 0.08]). Next, using generalized estimation equa-
tions, we examined whether the lag of the well-being variables
predicted: (a) engagement with the arts in general (0 ⫽no, 1 ⫽
yes), and (b) engagement with each of the arts categories (e.g.,
visual arts: 0 ⫽no, 1 ⫽yes). The lag of life satisfaction (but not
emotional well-being or meaning in life) was a significant negative
predictor of engaging with the arts in general (B⫽⫺0.49, SE ⫽
0.21, Wald Z(1) ⫽5.49, p⫽.019, 95% CI [⫺0.90, ⫺0.08]). The
lag of life satisfaction was also a negative predictor of engaging
with live arts (B⫽⫺
0.76, SE ⫽0.32, Wald Z(1) ⫽5.78, p⫽.016,
95% CI [⫺1.38, ⫺0.14]). Engagement with the other arts catego-
ries was not predicted by any of the well-being lag variables.
Summary of findings. The experience-sampling method used
in Study 2 showed that individuals had encounters with art on over
two thirds of sampled half days and spent a daily average of 2.3 hr
engaging with the artistic imagination of others, which was sub-
stantial but less than in Study 1. Engaging with art (vs. not
engaging) during a half day, spending more of a half day engaged
with art, and experiencing greater elevating feelings in response to
art during a half day were all positively associated with all aspects
of well-being, unlike sports spectating. Like Study 1, live arts
produced the strongest elevating experiences and had positive
associations with well-being, as did visual and literary arts; yet as
Table 3
Multilevel Regression Analysis Testing the Fixed Effects of Engaging (Versus Not Engaging)
With Different Art/Sport Activities on Well-Being in Study 2
Variables in models SE t df p CI-L CI-U
Emotional well-being
Age 0.01 0.01 1.52 49 .134 [⫺0.01, 0.03]
Income 0.11 0.21 0.51 48 .615 [⫺0.33, 0.54]
Visual arts 0.16 0.10 1.50 751 .133 [⫺0.05, 0.35]
Live arts 0.47 0.13 3.58 656 ⬍.001 [0.21, 0.74]
Literary arts 0.08 0.09 0.86 737 .388 [⫺0.10, 0.27]
Audio arts 0.13 0.08 1.66 756 .096 [⫺0.02, 0.27]
Screen arts 0.08 0.03 1.29 642 .196 [⫺0.04, 0.21]
Sports (spectating) ⫺0.02 0.06 ⫺0.23 744 .822 [⫺0.22, 0.17]
Life satisfaction
Age 0.01 0.01 1.02 47 .311 [⫺0.01, 0.04]
Income 0.53 0.28 1.89 47 .065 [⫺0.03, 1.09]
Visual arts 0.20 0.11 1.74 765 .082 [⫺0.02, 0.42]
Live arts 0.30 0.15 2.07 679 .038 [0.02, 0.59]
Literary arts 0.15 0.10 1.44 752 .150 [⫺0.05, 0.35]
Audio arts ⫺0.05 0.08 ⫺0.66 766 .513 [⫺0.22, 0.11]
Screen arts 0.10 0.07 1.46 665 .146 [⫺0.04, 0.24]
Sports (spectating) ⫺0.01 0.11 ⫺0.05 758 .957 [⫺0.22, 0.21]
Meaning in life
Age 0.17 0.13 1.38 47 .174 [⫺0.01, 0.04]
Income 0.45 0.28 1.58 47 .121 [⫺0.12, 1.03]
Visual arts 0.18 0.09 2.05 765 .041 [0.01, 0.35]
Live arts 0.25 0.11 2.17 698 .030 [0.02, 0.47]
Literary arts 0.16 0.08 1.96 756 .050 [0.01, 0.31]
Audio arts ⫺0.08 0.06 ⫺1.21 763 .228 [⫺0.20, 0.05]
Screen arts 0.05 0.05 0.99 686 .321 [⫺0.05, 0.16]
Sports (spectating) 0.04 0.09 0.42 760 .675 [⫺0.13, 0.20]
Note. 95% confidence interval: Lower (CI-L), Upper (CI-U) bounds. Coding: Income (household)— below UK
median (0), above UK median (1); engaged with activity—not engaged (0), engaged (1).
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9
ENCOUNTERS WITH ART AND WELL-BEING
in Study 1 they were less frequently engaged with than audio and
screen arts, which showed no significant associations with well-
being. An assessment of whether well-being also acts as a precur-
sor of arts engagement showed no significant association between
any well-being variable and the amount of time subsequently spent
on arts engagement and found that lower (not higher) levels of life
satisfaction were associated with subsequent acts of engagement
with the arts in general and live arts in particular.
Study 3
Having established in Studies 1 and 2 that encounters with live
arts have reliable relationships with all aspects of well-being, our
third study used a large publicly archived dataset to examine
whether frequency of attendance at live arts events during a year
had a longitudinal relationship with well-being 3 years later. Study
3 compared this relationship with those arising from frequency of
participation in creative arts (i.e., participatory art) and sports of
moderate intensity, and examined whether well-being led to atten-
dance (i.e., reverse causal path). An advantage of the large-scale
nature of the dataset was that it enabled us to exclude potential
confounding influences by including a large set of control vari-
ables. For this purpose, we replicated the set used by Wheatley and
Bickerton (2017) who used the same data source to examine the
cross-sectional relationship between arts engagement and well-
being. For our well-being measure, we extended their selection of
one item from the General Health Questionnaire to use all items
from the available scale (GHQ-12; Goldberg, 1972).
Method
Participants. We used data from participants who took part in
Waves 2 (2010 –2011) and 5 (2013–2014) of the Understanding
Society longitudinal panel survey. Understanding Society is a
research initiative funded by the U.K. Economic and Social Re-
search Council and various Government Departments, with scien-
tific leadership by the Institute for Social and Economic Research
(ISER), University of Essex, and survey delivery by NatCen Social
Research and Kantar Public. The research data are distributed by
the U.K. Data Service (University of Essex, Institute for Social and
Economic Research, NatCen Social Research, & Kantar Public,
2016). The dataset is a nationally representative annual survey of
40,000 households, gathered via face-to-face and telephone inter-
views. Waves 2 and 5 were used because, unlike other waves, both
contained data on the arts (participatory and receptive) and well-
being, allowing us to test for longitudinal associations while con-
sidering a large set of control variables. Our sample consisted of
27,918 individuals (57% female, 43% male) who had completed
the well-being measure at both waves, with a mean age of 47.55
years (SD ⫽17.12, Range: 16 –98). Of the sample, the majority
(58%) were working, 14% were economically inactive (e.g., un-
employed, long-term illness/disability), 6% were in education or
training, and 22% were retired.
Measures.
(Live) arts engagement. Participants indicated their atten-
dance (yes vs. no) at 14 art events (film at a cinema or other venue;
exhibition or collection of art, photography, sculpture or a craft
exhibition; event which included video or electronic art; event
connected with books or writing; street arts or a public display or
installation; carnival or festival; circus; play/drama, pantomime or
musical; opera; ballet; contemporary dance; African or South
Asian and Chinese dance; rock, pop or jazz performance; classical
music performance) over the past 12 months. If they answered
affirmatively, they indicated how frequently they had attended
events like that (as a whole) during the past 12 months from 1 (at
least once a week)to5(once in past year). We recoded the
frequency score to include participants who had not attended any
arts activities (6 ⫽did not do activity). Lower scores therefore
represent greater engagement with (live) arts events over the past
year.
Arts participation. Participants indicated their participation
(yes vs. no) in 14 arts activities (danced; sang; played a musical
instrument; wrote music; painting, drawing, printmaking or sculp-
ture; photography, film or video making; used a computer to create
artwork; rehearsed/performed in a play/drama, opera/operetta or
musical theater; performed in a carnival or street arts event;
learned or practiced circus skills; crafts; read for pleasure; took
part in a book club; wrote story, play or poetry) over the past 12
months. If they answered affirmatively, they indicated how fre-
quently they had taken part in activities like that (as a whole)
during the past 12 months from 1 (at least once a week)to5(once
in past year). We recoded the frequency score to include partici-
pants who had not participated in any arts activities (6 ⫽did not
do activity). Lower scores therefore represent greater participation
in arts activities over the past year.
Sports participation (moderate intensity sports). Participants
indicated their participation (yes vs. no) in 29 sporting activities
(e.g., gymnastics, boxing, martial arts, netball, hockey, ice-skating,
yoga or Pilates) over the past 12 months. If they answered affir-
matively, they indicated how frequently they had taken part in
those sports (as a whole) during the past 12 months from 1 (3⫹
times a week)to6(once in past year). We recoded the frequency
score to include participants who had not taken part in any sports
(7 ⫽did not do activity). Lower scores therefore represent greater
participation in moderate intensity sports over the past year.
Well-being. Well-being was indexed with the 12-item General
Health Questionnaire (GHQ-12; Goldberg, 1972), which is a scale
used to detect psychiatric disorder in the general population. Par-
ticipants rated whether they have experienced a particular symp-
tom or behavior recently compared to usual. Items included pos-
itive and negative symptoms/behaviors (e.g., “Have you recently
felt capable of making decisions about things?” and “Have you
recently lost much sleep over worry?”). Responses were made on
4-point scales which differ according to the specific question type
(e.g., 1 [more so than usual]to4[much less capable]and1[not
at all]to4[much more than usual] for the example items given
above). Items were recoded intoa0to3scale and items were
summed to create an overall score (ranging from 0 to 36) where
higher scores indicate more psychological distress and lower
scores indicate better psychological well-being.
Control variables. We selected the same control variables
that were used in a previous research study examining arts and
well-being with the Understanding Society dataset (Wheatley &
Bickerton, 2017). The following control variables from Wave 2
were included: age, gender (0 ⫽female, 1 ⫽male), long-term
illness or disability (0 ⫽no, 1 ⫽yes), highest educational
qualifications (reference ⫽no qualifications), marital status
(reference ⫽single/never married or in a civil partnership),
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10 TOTTERDELL AND POERIO
dependent children (0 ⫽no, 1 ⫽yes), government office region
(reference ⫽London), current economic activity (reference ⫽
economically inactive), annual labor income, working hours,
and overtime hours.
Results
Does arts engagement predict well-being? We were primar-
ily interested in whether (live) arts engagement would show a
longitudinal relationship with well-being. We therefore ran a re-
gression model with Wave 2 (W2) arts engagement predicting
Wave 5 (W5) well-being (GHQ). W2 arts engagement was entered
in Block 1 and W2 well-being, W2 sports participation and our
control variables were entered in Block 2. Results showed that arts
engagement at W2 was a significant predictor of later well-being
at W5, even after accounting for well-being at W2, sports partic-
ipation and control variables (summarized in Table 4). More
frequent arts engagement was associated with less psychological
distress/greater well-being (B⫽.07, SE ⫽.02, ⫽.02, t⫽3.00,
p⫽.003, 95% CI [.03, .12]).
Reverse causation: Does well-being predict arts engagement?
We were also interested in whether well-being would predict later
(live) arts engagement. We ran a regression model with W2
well-being predicting W5 arts engagement. W2 well-being was
entered in Block 1, and W2 arts engagement, W2 sports partici-
pation and the control variables were entered in Block 2. Results
showed that well-being at W2 was a significant predictor of
subsequent arts engagement at W5, even after accounting for prior
arts engagement at W2, sports participation and control variables.
Greater W2 well-being predicted more frequent live arts engage-
ment at W5 (B⫽0.01, SE ⫽0.01, ⫽0.02, t⫽4.25, p⬍.001,
95% CI [.00, .01]). See Table S3 in the online supplementary
materials.
Is arts engagement a stronger predictor of well-being than
arts participation? Finally, we were interested in whether (live)
arts engagement would show a stronger longitudinal relationship
with well-being compared to participating in arts (i.e., encounter-
ing vs. creating art). To examine this, we ran a regression model
with W2 arts engagement and participation predicting W5 well-
Table 4
Multiple Regression Analysis Testing the Predictive Effect of Wave 2 Frequency of Arts
Attendance on Wave 5 Mental Well-Being in Study 3
Predictor variables in model BSEB tp 95% CI
Block 1 R
2
⫽.005, F(1, 24,718) ⫽114.52, p⬍.001
Arts frequency (W2) 0.26 0.02 0.07 10.70 ⬍.001 [0.21, 0.30]
Block 2 (all W2) R
2
⫽.23, F(30, 24,718) ⫽240.76, p⬍.001
Arts frequency 0.07 0.02 0.02 3.00 .003 [0.03, 0.12]
Well-being 0.44 0.01 0.43 72.99 ⬍.001 [0.43, 0.45]
Sports frequency 0.05 0.01 0.02 3.62 ⬍.001 [0.02, 0.08]
Age ⫺0.02 0.00 ⫺0.05 ⫺4.89 ⬍.001 [⫺0.02, ⫺0.01]
Gender (0 female, 1 male) ⫺0.59 0.07 ⫺0.05 ⫺8.95 ⬍.001 [⫺0.72, ⫺0.46]
Long term illness/disability (0 no, 1 yes) 2.25 0.21 0.07 10.95 ⬍.001 [1.85, 2.65]
Highest qualification (vs. none)
Degree or equivalent ⫺0.24 0.11 ⫺0.02 ⫺2.12 .034 [⫺0.46, ⫺0.02]
A level ⫺0.25 0.12 ⫺0.02 ⫺2.15 .031 [⫺0.49, ⫺0.02]
GCSE ⫺0.09 0.11 ⫺0.01 ⫺0.78 .438 [⫺0.31, 0.13]
Marital status (vs. single/never)
Married/civil partner ⫺0.17 0.09 ⫺0.01 ⫺1.77 .077 [⫺0.35, 0.02]
Separated/divorced/former civil partner 0.29 0.14 0.01 2.08 .037 [0.02, 0.57]
Widowed/surviving civil partner ⫺0.33 0.18 ⫺0.01 ⫺1.86 .063 [⫺0.68, 0.02]
Dependent children (0 no, 1 yes) ⫺0.10 0.25 0.00 ⫺0.41 .685 [⫺0.59, 0.39]
Region (vs. London)
North East 0.22 0.19 0.01 1.19 .236 [⫺0.15, 0.60]
North West 0.12 0.14 0.01 0.88 .381 [⫺0.15, 0.40]
Yorkshire & Humber 0.22 0.15 0.01 1.42 .156 [⫺0.08, 0.52]
East Midlands ⫺0.07 0.15 0.00 ⫺0.44 .661 [⫺0.37,0.23]
West Midlands 0.17 0.15 0.01 1.11 .269 [⫺0.13, 0.47]
East of England ⫺0.35 0.15 ⫺0.02 ⫺2.36 .018 [⫺0.63, ⫺0.06]
South East 0.08 0.13 0.01 0.61 .542 [⫺0.18, 0.35]
South West 0.05 0.15 ⬍.01 0.35 .730 [⫺0.24, 0.34]
Wales 0.20 0.15 0.01 1.32 .186 [⫺0.10, 0.50]
Scotland ⫺0.01 0.14 ⬍⫺0.01 ⫺0.04 .965 [⫺0.28, 0.27]
Northern Ireland ⫺0.21 0.16 ⫺0.01 ⫺1.31 .192 [⫺0.52, 0.10]
Current economic activity (vs. inactive)
Working ⫺0.20 0.13 ⫺0.02 ⫺1.57 .116 [⫺0.46, 0.05]
Education or training ⫺0.30 0.21 ⫺0.01 ⫺1.47 .141 [⫺0.71, 0.10]
Retired ⫺0.24 0.15 ⫺0.02 ⫺1.65 .099 [⫺0.53, 0.05]
Annual income (GBP 000s) ⬍.01 ⬍.01 ⬍.01 .09 .926 [⬍⫺0.01, ⬍.01]
Working hours ⬍.01 ⬍.01 0.01 1.06 .290 [⬍⫺0.01, 0.01]
Overtime hours ⬍⫺0.01 0.01 ⬍⫺.01 ⫺.01 .995 [⫺0.01, 0.01]
Note. GCSE ⫽general certificate of secondary education; GBP ⫽Great Britain Pound. The labels in the table
refer to low well-being (GHQ-12) and low arts/sport frequency.
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11
ENCOUNTERS WITH ART AND WELL-BEING
being. W2 arts engagement and participation were entered in
Block 1 and W2 well-being, W2 sports participation and our
control variables were entered in Block 2. Results showed that arts
engagement at W2 was a significant predictor of later well-being
at W5 (B⫽0.08, SE ⫽0.03, ⫽0.02, t⫽3.09, p⫽.002, 95%
CI [0.03, 0.12]) whereas arts participation at W2 was not a sig-
nificant predictor of later well-being (B⫽⫺0.01, SE ⫽0.02,
⫽⫺.01, t⫽⫺0.70, p⫽.485, 95% CI [⫺.05, .02]). These
results suggest that more frequent engagement with live arts was
predictive of greater well-being but frequency of participation in
arts was not. We compared the regression weight for arts engage-
ment with those for arts participation and sports participation
(Paternoster, Brame, Mazerolle, & Piquero, 1998). The regression
weight for arts engagement was significantly greater than that for
arts participation (Z⫽2.50, p⫽.010). There was no difference
between the regression weights of arts engagement and sports
participation (Z⫽0.91, p⫽.360).
Summary of findings. Greater frequency of attendance at live
arts events during a year predicted less psychological distress 3
years later (and vice versa). The magnitude of this salutogenic
effect was found to be equivalent to the effect of frequent partic-
ipation in sports of moderate intensity, and greater than the effect
of frequent participatory art activity.
General Discussion
Using three different types of study, we investigated the extent
to which people encounter artistic imagination in daily life and
how those encounters and associated emotional responses relate to
different aspects of their well-being. The findings contribute to
existing research concerning the impact of cultural engagement on
psychological outcomes, which has mostly focused on participa-
tory rather than receptive art activities.
The duration and variety of encounters with artistic imagination
was found to be substantial. Participants in Study 1 spent more
than 4 hr per day on average engaged with artistic imagination, and
in Study 2 participants reported encounters with artistic imagina-
tion on more than two thirds of sampled occasions (half days).
Research has estimated that people spend between 30 and 50% of
their waking hours preoccupied with the internal imaginative
world of their daydreams (Killingsworth & Gilbert, 2010; Klinger
& Cox, 1987), and our findings suggest that they may be spending
a further sizable portion (perhaps with some overlap) engaged with
other people’s imagination too. However, some caution is war-
ranted because the level of arts encounters that we found may have
been inflated by the type of participants who volunteered. The
studies may have appealed more to those with an interest in the
arts. In Study 1, we tried to partially offset this problem by
recruiting some of the sample at a multiday sports event. In Study
2, the commitment involved in taking part in an experience-
sampling study means that self-selection is likely to have been a
greater issue here, but the recorded levels of arts engagement
across 10 days were lower than in Study 1.
The results of the three studies were consistent in showing that
encounters with art had reliable positive associations with different
types of well-being, including eudaimonic, hedonic, and life sat-
isfaction. Although these relationships were statistically signifi-
cant, some caution is warranted regarding their practical signifi-
cance because the effect sizes were small. Small effect sizes in
Study 3 were not surprising because it used a long general-purpose
survey so “noise” in the data was expected, but even in Study 1
encounters with art explained less than 8% of the variance in
well-being. That said, Study 3 found that frequency of attendance
at arts events had a positive association with subsequent mental
well-being that was equivalent or greater than the effects of em-
ployment, marriage and education; stronger than the effect of
participative arts; and equivalent to the well-established positive
effect of participation in moderate intensity sport (Fox, 1999).
Studies 1 and 2 found that watching or listening to sports did not
relate to any well-being measure.
The findings show that the emotional quality of the experience
is important when considering the effects of engaging with differ-
ent art activities. Previous studies of cultural engagement have
mostly focused on frequency of activity (Gordon-Nesbitt, 2015, p.
56). In this investigation, we looked at whether the variety of
different art activities, incidence of activity (engage vs. not en-
gage) and duration of activity had effects on well-being, but we
also examined and found robust effects of experiencing elevating
feelings (e.g., inspired, enriched, emotionally moved) in response
to encounters with art. Other research has noted that being moved
appears to be linked to meaning making (Koopman, 2015) and
relates to perceived closeness with others (Schubert, Zickfeld, &
Seibt, & Fiske, 2018). Research on fiction indicates that emotional
engagement and transportation into a narrative are necessary for
fiction to produce socioemotional benefits (Djikic, Oatley, &
Moldoveanu, 2013; Johnson, 2012; Oatley, 2016), which may hold
for other forms of artistic imagination.
The results of the first two studies showed that the associations
with well-being depended on the type of art activity involved. Live
arts (e.g., music concerts and theater) had the most consistent
positive relationship with all aspects of well-being. This may stem
from the social nature of live arts because people are likely to
attend and observe live events in the company of others. In Study
2 participants engaged with art in general in the presence of other
people on just under half of occasions but on over 80% occasions
for live arts. In a study of leisure activities, Iwasaki (2006) found
that social/cultural leisure was the best predictor of mental health,
whereas relaxing leisure such as listening to music or reading was
the best predictor of coping with stress. Cultural activities that
have social aspects have been observed to increase happiness
(Wheatley & Bickerton, 2017). This relationship was reinforced by
Study 2, which found that engaging with the arts activity in a social
(vs. nonsocial) context was associated with hedonic well-being and
life satisfaction (but not eudaimonic well-being). Participatory art
in Study 3 involved a spectrum of activities so it may be that
effects on well-being would be found if participatory activities
with social content were examined separately. That is not to say
that social cultural activities are always associated with the stron-
gest positive effects on outcomes. For example, Väänänen et al.
(2009) found that solitary cultural activity had a more robust effect
for decreased all-cause mortality. The effect of live arts can also be
explained in other ways because it is consistent with enriched
environment theory (see Spencer, 1997) and could also be due to
the mental and physical investment required to attend live events.
Furthermore, on the issue of arts activity, the most common
encounters with artistic imagination in Studies 1 and 2 involved
audio and screen arts, yet these activities seemed least able to yield
positive effects on well-being, even though engagement with
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12 TOTTERDELL AND POERIO
screen arts frequently occurred in a social context. This lack of
association could stem from habituation due to greater time spent
on those categories, or from passive consumption that may occur
within them (e.g., watching or listening through habit). It may also
be necessary to look at subcategories of activity, at genres, and at
quality or complexity of content to reveal effects that may be
hidden when content is aggregated.
Limitations
A limitation of all three studies is that conclusive causal infer-
ences about the discovered relationships between encounters with
art and well-being cannot be drawn because they are based on
associations rather than changes in well-being in response to
manipulations of encounters with art. Studies 2 and 3 provide
stronger but not definitive evidence of causality. The multilevel
models in Study 2 used an autocorrelative structure, which means
that well-being on the previous occasion was accounted for. In
Study 3, live arts attendance was used to predict well-being at a
later timepoint (i.e., the measures were not simultaneous) and
baseline well-being was controlled for. Nevertheless, the associa-
tion between encounters with art and well-being could be due to
the former being a proxy of the latter. Gordon-Nesbitt (2015, p. 33)
observes that the gender differences found in previous related
research suggest that a proxy explanation is unlikely to be the case,
at least for health effects. The causal direction could be the reverse
of that supposed (Gordon-Nesbitt, 2015, p.55), meaning that poor
well-being may reduce arts engagement. One of the analyses in
Study 2 directly examined the impact of previous well-being on
arts engagement, finding no evidence of a relationship except for
life satisfaction which had a negative association suggesting that
dissatisfaction may have prompted more (not less) arts engage-
ment. There was some evidence of a bidirectional positive rela-
tionship between live arts attendance and well-being in Study 3.
A further limitation of our investigation concerns its conception
of receptive arts, which included video art but was otherwise
insufficiently inclusive of interactive arts (e.g., computer games,
virtual reality). The boundaries of our conception could also have
been extended to include artifacts that are not traditionally seen as
art yet arise from and stimulate people’s imagination (e.g., toys,
architecture). Alternatively, the conception of receptive arts may
prove to be more productive if it is completely changed so that it
is based on underlying processes rather than the form/medium of
the art (e.g., Brown, 2018).
Our examination of well-being was limited by not distinguish-
ing between the presence and search for meaning in life (Steger,
Kashdan, Sullivan, & Lorentz, 2008). These two components of
eudaimonic well-being may have different relations with arts en-
gagement. Specifically, engagement with art could be used to
pursue a perceived lack of meaning in life without necessarily
providing it.
Notwithstanding these limitations, this investigation provides
the first longitudinal examination of the impact of the receptive
arts on well-being. The findings show that: engagement with the
receptive arts is a substantial feature of daily life that is associated
with different types of well-being; the emotional experience aris-
ing from arts engagement contributes to its impact; and its precise
effect on well-being depends on the nature of the art activity which
may in part be due to the social context in which it occurs. Our
investigation also provides a unique conceptualization of receptive
arts that we believe may open a new line of research.
Future Research
We framed our investigation around the idea that receptive art
activities represent encounters with artistic imagination that influ-
ence people’s emotional experiences and well-being. Here we
extend that notion to theorize that engaging with artistic imagina-
tion affects well-being because it instigates a process of mental
simulation, in which people connect their own experiences to those
imagined in the art, and consequently experience an aesthetic
emotional, and cognitive response. Mental simulation is “the pro-
cess of self-projection into alternate temporal, spatial, social, or
hypothetical realities” (Waytz, Hershfield, & Tamir, 2015, p.336),
and as such might be involved in both creating and engaging with
(viz., receiving) art.
According to Baumeister and Masicampo (2010), people use
mental simulations to understand themselves and others. In support
of this view, Zhou, Majka, and Epley (2017) found that mentally
simulating other people’s perspective provides greater accuracy in
emotional understanding than inferring their perspective. Simula-
tions enable people to learn about social situations by allowing
them to process cultural information (Baumeister & Masicampo,
2010). This cultural information can be transmitted through art
(Oatley, 2016). For example, Tamir, Bricker, Dodell-Feder, and
Mitchell (2016) found that frequent fiction readers had better
social– cognitive performance, an association mediated by the neu-
ral networks underpinning mental simulation. Similarly, Vessel,
Starr, and Rubin (2013) used neurophysiological evidence to sup-
port the proposition that art “moves people from within” through
stimulating self-relevant neural processing. Engaging in mental
simulation has been related to personal well-being in the form of
experiencing a greater sense of meaning in life (Waytz et al.,
2015). However, our investigation did not test whether simulation
occurs or is responsible for the effects of arts engagement on
well-being. This omission offers an exciting research initiative to
pursue in future.
Part of that initiative should explore whether both mental sim-
ulation and allied aesthetic responses are needed to account for the
effects of arts engagement on well-being, or whether one alone is
both necessary and sufficient to explain its effects. A difficulty for
a simulation account is that it does not locate a felt response, but
a difficulty for an aesthetic emotion account is that it does not
locate the source of a personal aesthetic. Other accounts have
emphasized that responses to art are based on vicarious rather than
actual experience (Kawakami, Furukawa, & Okanoya, 2014) or
require people to distance themselves prior to embracing the
stimulus (Menninghaus et al., 2017). According to Menninghaus
and colleagues, embracing art entails an interplay of positive
emotions and negative emotions and meaning making that renders
it moving and profound. These accounts may offer alternative or
complementary explanations of our findings.
Future research should also consider individuals’ motivations
for engaging with art. Wilson et al. (2014) found that people do not
typically find the company of their own thoughts pleasurable, even
though they can derive personal benefits from using their own
imagination, including enhancing well-being through daydreaming
(Mar, Mason, & Litvack, 2012; Poerio, Totterdell, Emerson, &
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13
ENCOUNTERS WITH ART AND WELL-BEING
Miles, 2015). It seems that people prefer to engage in leisure
activities, such as reading or watching TV (Fox, Thompson,
Andrews-Hanna, & Christoff, 2014), rather than just think when
given the choice. However, such activities may provide a straight-
forward means through which people engage with others’ imagi-
nation and thereby enrich their own. Individual differences in
choice and outcome of such engagement is likely. For instance,
what individuals classify as art differs (Pelowski, 2015) and there-
fore their expectations of it in relation to themselves and its effects
are likely to differ. Individuals’ choice of art activity is also likely
to differ according to their emotional motives. For example, Miu,
Pitur, and Szentágotai-Ta
˘tar (2016) found that music is used more
frequently than paintings to repair emotions.
Conclusion
The potential contribution of the arts to health and well-being
has been recognized in recent national policy reports that have
reviewed relevant research and interventions (e.g., United King-
dom: Gordon-Nesbitt, 2015; Australia: Mills, 2011). A cultural
attendance program, for example, involved health trainers refer-
ring people to events happening at local cultural institutions to aid
their mental health (Froggett & Roy, 2014). The findings of our
investigation vindicate the development and expansion of such
interventions to include other receptive arts. Moreover, the re-
search makes it apparent that encounters with artistic imagination
are part and parcel of everyday life for good psychological reason.
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Received February 16, 2019
Revision received March 31, 2020
Accepted April 2, 2020 䡲
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