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Different Stories: How Levels of Familiarity With Literary and Genre Fiction Relate to Mentalizing.

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Our ability to infer and understand others’ thoughts and feelings, known as theory of mind (ToM), has important consequences across the life span, supporting empathy, pro-social behavior, and coordination in groups. Socialization practices and interpersonal interactions help develop this capacity, and so does engaging with fiction. Research suggests that lifetime exposure to fiction predicts performance on ToM tests, but little evidence speaks to the type of fiction most responsible for this effect. We draw from literary theory and empirical work to propose that literary fiction is more likely than genre fiction to foster ToM, describe the development of a new method for assessing exposure to literary and popular genre fiction, and report findings from 3 samples testing the specificity of the relation between exposure to literary fiction and ToM. Results indicate that exposure to literary but not genre fiction positively predicts performance on a test of ToM, even when accounting for demographic variables including age, gender, educational attainment, undergraduate major (in 2 samples), and self-reported empathy (in 1 sample). These findings offer further evidence that habitual engagement with others’ minds, even fictional ones, may improve the psychological processes supporting intersubjectivity. We discuss their implications for understanding the impacts of fiction, and for models of culture more generally.
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Psychology of Aesthetics, Creativity, and the
Arts
Different Stories: How Levels of Familiarity With Literary
and Genre Fiction Relate to Mentalizing
David Kidd and Emanuele Castano
Online First Publication, August 8, 2016. http://dx.doi.org/10.1037/aca0000069
CITATION
Kidd, D., & Castano, E. (2016, August 8). Different Stories: How Levels of Familiarity With
Literary and Genre Fiction Relate to Mentalizing. Psychology of Aesthetics, Creativity, and the
Arts. Advance online publication. http://dx.doi.org/10.1037/aca0000069
Different Stories: How Levels of Familiarity With Literary and Genre
Fiction Relate to Mentalizing
David Kidd and Emanuele Castano
The New School for Social Research
Our ability to infer and understand others’ thoughts and feelings, known as theory of mind (ToM),
has important consequences across the life span, supporting empathy, pro-social behavior, and
coordination in groups. Socialization practices and interpersonal interactions help develop this
capacity, and so does engaging with fiction. Research suggests that lifetime exposure to fiction
predicts performance on ToM tests, but little evidence speaks to the type of fiction most responsible
for this effect. We draw from literary theory and empirical work to propose that literary fiction is
more likely than genre fiction to foster ToM, describe the development of a new method for
assessing exposure to literary and popular genre fiction, and report findings from 3 samples testing
the specificity of the relation between exposure to literary fiction and ToM. Results indicate that
exposure to literary but not genre fiction positively predicts performance on a test of ToM, even
when accounting for demographic variables including age, gender, educational attainment, under-
graduate major (in 2 samples), and self-reported empathy (in 1 sample). These findings offer further
evidence that habitual engagement with others’ minds, even fictional ones, may improve the
psychological processes supporting intersubjectivity. We discuss their implications for understand-
ing the impacts of fiction, and for models of culture more generally.
Keywords: culture and cognition, fiction, individual differences, person perception, theory of mind
The ability to engage with others on the basis of their subjective
experiences is critical to living a normal social life. A growing
literature emphasizes the importance of constructs such as empa-
thy, concern for the thoughts and feelings of others (de Waal,
2008); and emotional intelligence, the ability to effectively inte-
grate understanding of one’s own and others’ emotions into
decision-making (Mayer, Roberts, & Barsade, 2008). At the core
of this capacity for intersubjectivity is theory of mind (ToM), the
ability to represent the mental states of others (Heyes & Frith,
2014). In much research, ToM is assessed by administering the
Reading the Mind in the Eyes Test (RMET; Baron-Cohen, Wheel-
wright, Hill, Raste, & Plumb, 2001), which asks participants to
select which of four emotion terms most closely matches the
expression of a person in a photograph. Studies using this measure
indicate that deficits in ToM are associated with pathologies in-
cluding autism and schizophrenia (Baron-Cohen, Leslie, & Frith,
1985; Brüne, 2005), just as better performance on tests of ToM
relates to more prosocial (Declerck & Bogaert, 2008) and effective
social interactions (Engel, Woolley, Jing, Chabris, & Malone,
2014; Woolley, Chabris, Pentland, Hashmi, & Malone, 2010).
Given the importance of ToM, researchers have begun to ex-
amine potential sources of variation in this capacity. For instance,
individuals who are asked to think of themselves as having high
socioeconomic status (SES) perform worse on an advanced test of
ToM than those given low SES instructions, apparently because
the high status manipulation reduced their perceived need to attend
to others (Kraus, Côté, & Keltner, 2010). In contrast, a compassion
meditation training program, intended to promote more careful
attention to others’ experiences, led to better performance on the
same ToM test compared to a control discussion group (Mascaro,
Rilling, Negi, & Raison, 2013). These studies suggest that ToM is
not just a developmental achievement, but also a capacity that is
modulated by situations or activities that direct attention to others’
mental states. Engagement with fictional narratives is one such
activity.
Research has revealed that familiarity with fiction authors, a
good proxy measure of actual reading habits, correlates with scores
on a test of ToM (Mar et al., 2006), and that this relation is not
explained by individual differences in agreeableness or a disposi-
tional tendency to imagine oneself in fictional worlds (Mar, Oat-
ley, & Peterson, 2009). As Mar and Oatley (2008) argue, fiction
supports rich simulations of social worlds, providing readers with
opportunities to hone the processes underlying social perception
(see also Koopman & Hakemulder, 2015). Just as real world
interactions do not reliably require intensive reliance on ToM
(Hirschfeld, 2006), however, different types of fiction also appear
David Kidd and Emanuele Castano, Department of Psychology, The
New School for Social Research.
This research was supported by the Whiting Foundation.
Correspondence concerning this article should be addressed to David
Kidd or Emanuele Castano, Department of Psychology, New School for
Social Research, 80 Fifth Avenue, New York, NY 10011. E-mail:
kiddd305@newschool.edu or castanoe@newschool.edu
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.
Psychology of Aesthetics, Creativity, and the Arts © 2016 American Psychological Association
2016, Vol. 10, No. 3, 000 1931-3896/16/$12.00 http://dx.doi.org/10.1037/aca0000069
1
to make varying demands on ToM processes, with literary fiction
being most likely to strongly evoke ToM (Kidd & Castano, 2013).
The importance of distinguishing between literary and genre
fiction is highlighted by scholarship that draws from both literary
studies and psychological theory. Genre fiction is defined primar-
ily by its focus on a particular topic and reliance on relatively
formulaic plots. By contrast, literary fiction is defined more by its
aesthetic qualities and character development than its focus on plot
or a particular set of topics and themes. This distinction is recog-
nized by publishers, who routinely list it as a publishing category;
and by critics, who award separate prizes for specific genres (e.g.,
the Hugo awards for fantasy and the Nebula awards for science
fiction), as well as prizes for general literary quality (e.g., the
PEN/O. Henry Prize and the National Book Award for fiction).
The distinction has also been put in terms of what attracts readers
to the work: entertainment and escape for genre fiction, under-
standing and engagement for literary fiction (Petite, 2014). Em-
pirical research appears to bear this out. A study of adult readers
found that readers of primarily literary, romance, or mystery
fiction value different features. Readers of literary fiction, com-
pared to the others, indicated greater appreciation for figurative
language (e.g., metaphor), multiple plot lines, many possible
meanings, opportunities for imaginative interpretation, several
shifting perspectives, and character development (Miesen, 2004).
Although there are certainly exceptions and ambiguous cases,
industry, critics, and ordinary readers appear to agree that literary
fiction generally affords greater opportunities for interpretive en-
gagement than more formulaic genres.
This view resonates with extant theory and research. The cog-
nitive literary theorist David Herman (1997) proposes that all
fiction makes use of psychological schemas and scripts, with
variation in usage “correspond[ing] to generic classifications” (p.
1054). However, he notes that the “processing of narratives is
more complex when they inhibit what might be termed the naïve
application of scripts and promote instead reflection on the limits
of applicability of the scripts being invoked” (p. 1054). That is,
part of what differentiates literary and genre fiction may be their
relative degrees of uncritical reliance on widely shared scripts,
schemas, and stereotypes. Consistent with this view, a study of TV
viewing habits found that watching formulaic genre dramas was
positively associated with conventional thinking (Appel, 2008).
Other scholars have argued that many, perhaps most, works of
fiction tend to present clear protagonists and antagonists who
display fixed traits associated with their agonistic role (Carroll,
Gottschall, Johnson, & Kruger, 2012). Easily understood and
predictable characters are thought to bolster readers’ social confi-
dence (Gerrig & Rapp, 2004), and contribute to an existentially
reassuring experience of stability and order (Nell, 2002).
Yet, research also suggests that some fiction, particularly liter-
ary fiction, may support a different range of experiences and
psychological effects. Drawing from the formalist concept of de-
familiarization, Miall and Kuiken (1994, 1999) propose that liter-
ary qualities tend to disrupt routine or rigid modes of thinking.
Experimental work supports this and Herman’s (1997) argument,
with participants assigned to read literary fiction reporting reduced
need for order and greater tolerance for ambiguity than those
assigned to read nonfiction (Djikic, Oatley, & Moldoveanu, 2013).
When it comes to characterization, literary fiction tends to flout
polarized agonistic structures or discrete personalities, developing
instead complex characters (Hakemulder, 2000). Suzanne Keen
(2011), while criticizing the high/low evaluative distinction be-
tween literary and popular genre fiction, recognizes that the two
forms differ in terms of characterization, with “sketchy and ste-
reotyped characters engaged in predictable actions typifying
despised lowbrow genres and complicated, changeable, and
category-resistant characters populating serious literary fiction” (p.
303). Eder, Jannidis, and Schneider (2010) likewise observe that
despite a longstanding critical preference for complex characters,
popular formulaic genres across media continue to place stock
characters in central roles.
These depictions of characterization in literary and popular
fiction align with a distinction made by the writer and critic E. M.
Forster (1927/2002) between round and flat characters. In Forst-
er’s (1927/2002) view, flat characters are simple and predictable,
whereas round characters are more psychologically interesting and
thus greater artistic achievements. However, Keen (2011) notes
that simple characters sometimes evoke strong feelings of empathy
precisely because their struggles and triumphs are unclouded by
ambiguity. Therefore, although flat and round characters may each
effectively attract readers, multidimensional, round characters are
more reliable sources of the interpretive richness that is favored by
contemporary critics and readers of literary fiction (Miesen, 2004).
To understand how each type of character engages readers,
Culpeper (2001) discusses flat and round characters in terms of
category-based and person-based perception, respectively. Flat
characters are easily recognized and represented in terms of a
single role or idea; they are types and caricatures. Along with
Culpeper (2001), we propose that the rapid identification and
elaboration of flat characters draws on readers’ extensive famil-
iarity with schemas associated with different social identities and
roles, as well as with particular stock characters associated with
specific genres. Hirschfeld (2006) labels this capacity to navigate
the social world on the basis of schematic information, Theory of
Society, and observes that it is often a more rapid, efficient, and
(sometimes) accurate means to understanding others than ToM.
That is, just as in the real world, readers may effectively make
sense of fictional worlds by applying prior schematic knowledge.
This strategy seems especially likely when those fictional worlds
are constructed using established formulas and populated with
fairly stock characters.
In contrast, Culpeper (2001) argues that round characters are
less likely to be understood as types, instead prompting person-
based, or individuated, perception. Unlike impressions based on
applications of schemas, those formed via individuation involve
regular updates and adjustments as new information is acquired
about the individual’s particular beliefs, feelings, and intentions
(Swencionis & Fiske, 2014). Round characters cannot be readily
understood in terms of a particular schema, and thus readers must
consistently attend to cues to their mental states. Moreover, in
literary fiction, these cues are often subtle (Zunshine, 2015), add-
ing to the reader’s inferential task. Thus, literary fiction, with its
generally less easily understood characters (Hakemulder, 2000;
Keen, 2011), is more likely than popular genre fiction to exten-
sively recruit bottom-up, person-based sociocognitive processes.
Consistent with this view, recent experimental work shows that
it is engaging with literary fiction specifically that enhances per-
formance on ToM tests; engagement with genre fiction does not
(Kidd & Castano, 2013). These findings raise the possibility that
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2KIDD AND CASTANO
the positive correlation between familiarity with fiction and ToM
that has been repeatedly observed (e.g., Mar et al., 2006, 2009)
could in fact be primarily attributable to familiarity with literary
fiction. In one study in which participants completed an ART with
subscales for different genres (i.e., domestic, romance, science-
fiction/fantasy, and suspense), only familiarity with romance fic-
tion positively predicted ToM performance (Fong, Mullin, & Mar,
2013). However, no measure of exposure to specifically literary
fiction was included, making it impossible to assess the relative
contributions of literary and genre fiction to ToM.
Two studies were conducted to assess whether it is familiarity
with literary fiction specifically that predicts performance on a test
of advanced ToM, or whether familiarity with genre fiction is just
as important a predictor. Despite the theoretical differences be-
tween literary and genre fiction, it is unclear whether this distinc-
tion is consistently reflected in ordinary readers’ patterns of expo-
sure to fiction. To address this question, we first conducted a factor
analysis of a well-validated ART (Acheson, Wells, & MacDonald,
2008) in two separate samples. Utilizing factor analysis is impor-
tant for theoretical and methodological reasons. In terms of theory,
identifying literary and genre factors would suggest that ordinary
readers (or at least their sources of reading recommendations) are
sensitive to the distinction between literary and genre fiction. From
a methodological perspective, factor analysis is important to es-
tablish that recognition rates of literary and genre authors are
empirically distinguishable, and that they correspond to separate
underlying constructs. In addition, adopting this data-driven ap-
proach to classifying authors as literary or genre is more method-
ologically objective than more subjective methods. After identify-
ing factors corresponding to literary and genre fiction, scores based
on recognition rates of authors loading onto these factors were
used to test the relations of familiarity with each type of fiction
with ToM performance in three samples.
Study 1
Method
Participants and procedures.
Sample 1. Participants (N1,260) in the first sample were
recruited via an embedded link in a New York Times article
(Belluck, 2013) about research on reading fiction and interpersonal
sensitivity. We aimed to secure between 15 and 20 cases for each
of the 65 critical items of the instrument measuring familiarity
with fiction, the Author Recognition Test (ART), to ensure reli-
ability of the factor analytical procedure, and we stopped data
collection once the response rate exceeded 1,200. Participants who
failed to select at least one author on the ART or selected more
foils than authors (n13) were removed, along with those who
did not provide demographic information (n4). All remaining
participants performed above chance on the RMET. Upon clicking
the embedded link, potential participants were directed to a Qual-
trics survey where, upon providing informed consent, they com-
pleted a test of ToM, the ART, and a series of demographic
questions including their gender, age, level of education, college
major, and race/ethnicity.
1
Level of education was assessed by
asking participants to indicate their highest attained degree using
the following options: some high school, high school graduate,
some college, college graduate, or graduate degree. To simplify
analyses, level of education was recoded into categories for those
without a college degree and those with a college degree. Partic-
ipants also indicated their undergraduate major by selecting one of
the following options: business, humanities, natural sciences, so-
cial sciences, or other. Upon completing the survey, participants
were thanked and shown their score on the ToM test.
Sample 2. Participants (N896) in the second sample were
recruited online using Amazon.com’s Mechanical Turk service
and were then directed to online studies hosted by Qualtrics.com
after providing informed consent. These were paid participants in
one of six experiments (four of which are reported in Kidd &
Castano, 2013) that included a common measure of ToM and the
measure of familiarity with fiction. In these experiments, some
participants were randomly assigned to read literary fiction (n
340) and others were assigned to read nonfiction (n42), popular
genre fiction (n275), or nothing at all (n239) before
completing the test of ToM and familiarity measure. The overall
size of the second sample was based on convenience and power
considerations specific to the experiments from which the data was
obtained. The exclusion criteria for this sample are described in
Kidd and Castano (2013), and those for the experiments not
reported there are the same as in that report’s fifth experiment.
Characteristics of both samples are presented in Table 1.
Measures.
Theory of mind. Theory of mind was assessed using the
Reading the Mind in the Eyes Test (RMET; Baron-Cohen et al.,
2001). Designed and validated as a measure of advanced ToM, the
RMET includes 36 trials in which black and white images of only
the eye regions of the faces of actors are shown. Participants
respond by selecting which of four complex emotion terms (e.g.,
contemplative, cautious, concerned, irritated) best matches the
emotion expressed in each image. Unlike many tests of ToM,
which have largely been designed for use with children or people
with social difficulties, the RMET is sufficiently difficult to reveal
variability among ordinary adult participants (Baron-Cohen et al.,
2001; Vellante et al., 2013). The RMET is also distinct from more
simple tests of emotion perception because the mental states de-
picted are complex, often blending affective and cognitive features
(e.g., contemplative), and thus require advanced ToM in order to
be understood (Mitchell & Phillips, 2015; Singer, 2006).
Familiarity with fiction. The Author Recognition Test (ART)
is a measure of exposure to fiction originally developed by Stanov-
ich and West (1989). Participants are shown an extensive list of
names and asked to identify the authors they recognize. The
presence of an equal number of nonauthors and authors helps to
discourage guessing. Unlike self-reports of reading habits, this
form of measurement is less likely to be influenced by a desire to
present oneself as a more avid reader than is truly the case, and it
has been shown to effectively predict participants’ actual engage-
ment with fiction (Rain & Mar, 2014; Stanovich & Cunningham,
1992; Stanovich, West, & Harrison, 1995). Modified versions of
the ART have been used to distinguish rates of reading nonfiction
and fiction (e.g., Mar et al., 2006, 2009), as well as different genres
of fiction (e.g., Fong et al., 2013; Fong, Mullin, & Mar, 2015).
Participants in both of the current samples completed an updated
1
Participants also completed a measure of moral values, but those data
are not discussed here.
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3
DIFFERENT STORIES
version of the ART (Acheson et al., 2008) that includes 130 names,
65 of which are those of authors of fiction. In a recent study,
Moore and Gordon (2015) administered the same ART to a large
student sample and reported a two-factor solution for the ART
responses that roughly matches the distinction between literary and
genre fiction, suggesting the appropriateness of this measure for
the present study.
Results
Identification of literary and genre categories in the ART.
Sample 1. Because responses on the ART are dichotomous, an
iterated principal factors analysis (SAS v.9.2, Proc Factor) was
conducted on a tetrachoric correlation matrix (generated using the
%polychor macro for SAS [convergence criterion .0001, max-
imum iterations 25]). The number of factors was limited to two,
and an oblique transformation was used to account for the ex-
pected correlation of the factors.
The Eigenvalues were 35.32 and 4.27 for the first and second
factors, respectively. Together, the two factors accounted for
60.92% of the variance. Although other Eigenvalues were greater
than 1, only two were retained in order to maximize theoretical
interpretability. Following the recommendations outlined by
O’Rourke and Hatcher (2013), 32 authors were associated (pattern
loadings .40) with the first factor and 23 were associated only
with the second factor. Seven authors had loadings greater than the
threshold of 0.40 on both factors, and three had loadings of less
than 0.40 on both factors (see Table 2). The first factor was
composed almost exclusively of authors easily categorized as
literary (e.g., Toni Morrison, Vladimir Nabokov), whereas the
second factor included mostly authors of popular genre fiction
(e.g., Tom Clancy, Danielle Steel).
Sample 2. The same procedure described above was used for
the second sample (N896). The eigenvalue for the first factor
was 35.09 and 4.26 for the second, with the factors together
explaining 60.55% of the variance. Forty-three authors were asso-
ciated with the first factor and 18 authors with the second factor.
Only one author (Nora Ephron) had a loading greater than 0.40 on
both factors, and three authors had loadings of less than 0.40 on
both factors (see Table 2). As in the first sample, the first factor
represented primarily literary authors, whereas the second factor
included mostly genre authors.
Comparison of factor analyses. The factor analyses led to
substantially similar results in the two samples. Bivariate correla-
tions of the factor loadings from the two samples revealed that
both loadings on the literary factor, r(63) .83, p.001, and the
genre factor, r(63) .76, p.001, were highly correlated.
Moreover, only four (6.15%) authors were associated with differ-
ent factors in the two samples. In all cases, these authors (Maya
Angelou, Ernest Hemingway, E. B. White, and Thomas Wolfe)
loaded significantly only on the genre factor in the first sample and
only on the literary factor in the second sample.
Factor analysis with combined samples. Given the similarity
of these analyses, a final iterated factors analysis was conducted
after combining the data from both samples (N2,139). The
eigenvalue for the first factor was 36.15, and the eigenvalue for the
second was 3.95. Together, the two factors accounted for 61.72%
of the variance. Thirty-nine authors were identified as loading
(.40) onto the first factor, and 20 loaded only onto the second
Table 1
Sample Characteristics, Differences, and Correlations Among Variables for Study 1
Age
ART
ART foils
Literary ART
Genre ART
RMET
% College
graduates
% Women
% White
Sample 1 (N1,243) 44.09 (16.21)
[43.19, 44.99]
30.17 (16.20) [29.27, 31.07]
␣⫽.96
1.37 (2.46)
[1.23, 1.50]
.50 (.27) [.49, .52]
␣⫽.95
.44 (.28) [.42, .46]
␣⫽.91
26.35 (3.81) [26.13, 26.56]
␣⫽.56
74.12 71.78 82.56
Sample 2 (N896) 33.48 (11.45)
[32.73, 34.23]
21.64 (13.90) [20.73, 22.55]
␣⫽.96
.62 (1.49)
[.53, .72]
.34 (.23) [.32, .35]
␣⫽.94
.32 (.23) [.30, .34]
␣⫽.90
25.58 (4.37) [25.29, 25.86]
␣⫽.73
50.56 52.34 80.47
Age — .48
ⴱⴱⴱ
[.44, .52] .05 [.00, .10] .38
ⴱⴱⴱ
[.33, .42] .61
ⴱⴱⴱ
[.57, .64] .08
ⴱⴱ
[.13, .02] ——
ART .36
ⴱⴱⴱ
[.30, .42] .01 [.03, .07] .95
ⴱⴱⴱ
[.95, .96] .87
ⴱⴱⴱ
[.85, .88] .08
ⴱⴱ
[.03, .14] ——
ART Foils .03 [.02, .10] .10
ⴱⴱ
[.03, .16] — .15
ⴱⴱⴱ
[.09, .20] .16
ⴱⴱⴱ
[.11, .21] .00 [.05, .05]
Literary ART .23
ⴱⴱⴱ
[.16, .29] .96
ⴱⴱⴱ
[.95, .96] .19
ⴱⴱⴱ
[.13, .26] — .74
ⴱⴱⴱ
[.72, .77] .10
ⴱⴱⴱ
[.05, .16] ——
Genre ART .56
ⴱⴱⴱ
[.51, .60] .86
ⴱⴱⴱ
[.84, .88] .18
ⴱⴱⴱ
[.12, .24] .71
ⴱⴱⴱ
[.68, .74] .01 [.03, .07]
RMET .04 [.02, .11] .25
ⴱⴱⴱ
[.19, .31] .01 [.05, .08] .23
ⴱⴱⴱ
[.17, .29] .22
ⴱⴱⴱ
[.16, .28] ——
Note. ART Author Recognition Test; RMET Reading the Mind in the Eyes Test. Literary ART and Genre ART scores are calculated as proportions of authors recognized. Standard deviations
for each mean are reported in parentheses. 95% Confidence intervals for each mean are reported in brackets. Correlations for Sample 1 are reported above the diagonal.
In the top row indicates a difference between the samples significant at p.05.
ⴱⴱ
Indicates a correlation significant at p.01.
ⴱⴱⴱ
Indicates a correlation significant at p.001.
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4KIDD AND CASTANO
Table 2
Rotated Factor Pattern (Standardized Regression Coefficients)
Literary Genre % Selected
Author Sample 1 Sample 2 Combined Sample 1 Sample 2 Combined Combined
Gabriel Garcia Marquez 1.04108 .86278 1.03802 .3094 .045 .2719 34.39
Vladimir Nabokov .96056 .93354 .99769 .1916 .1356 .214 38.35
Umberto Eco .96741 .80742 .94308 .225 .12802 .1371 29.02
Kazuo Ishiguro .87958 .92431 .93895 .1506 .2291 .2151 14.13
Isabel Allende .87984 .55991 .88519 .1324 .22885 .1232 24.17
Samuel Beckett .82621 .78077 .85365 .0504 .00598 .06 39.80
Michael Ondaatje .8164 .72189 .85272 .02575 .1074 .0159 12.27
Thomas Pynchon .7789 .91693 .8523 .16375 .0084 .07801 25.29
Margaret Atwood .79022 .78109 .83615 .0518 .04858 .00572 38.54
Virginia Woolf .73283 .86822 .79068 .039 .1409 .0694 69.71
Ralph Ellison .68587 .74478 .75488 .07357 .0256 .00487 28.46
Alice Walker .68171 .62671 .75199 .17668 .15722 .0852 36.63
Toni Morrison .64914 .75442 .74429 .2761 .1079 .16272 43.58
James Joyce .65456 .85347 .73521 .24152 .04258 .17141 60.24
Saul Bellow .65437 .74758 .72995 .33549 .22887 .25284 27.62
Joyce Carol Oates .65353 .72372 .72602 .31788 .20339 .22946 40.27
Bernard Malamud .63781 .81442 .702 .25952 .2233 .21614 13.90
George Orwell .66356 .8292 .68755 .13993 .1785 .06412 80.82
Ann Beattie .63523 .47555 .67743 .14296 .16452 .07829 11.43
Raymond Chandler .64969 .70388 .67481 .23352 .21859 .22356 26.45
John Irving .628 .55313 .6702 .16487 .20701 .12288 48.39
Paul Theroux .63161 .51103 .66711 .13468 .15274 .07869 24.73
T. C. Boyle .62811 .44815 .66599 .1115 .08709 .128 20.34
Harper Lee .55369 .83851 .66398 .24863 .1978 .08003 55.15
Jane Smiley .60096 .647 .65375 .32292 .32645 .27566 13.48
F. S. Fitzgerald .52657 .82115 .64987 .27404 .1605 .10345 83.06
Salman Rushdie .5703 .6895 .63249 .32876 .20581 .27689 48.62
Kurt Vonnegut .51744 .84797 .61283 .42196 .01498 .29425 62.01
William Faulkner .50129 .69975 .59437 .36959 .1364 .27222 65.84
Willa Cather .5087 .60223 .59147 .47297 .34526 .38052 28.83
Isaac Asimov .55299 .67597 .56923 .31297 .13098 .27798 59.58
J. D. Salinger .43898 .77438 .52534 .4436 .02444 .32011 73.96
Ayn Rand .42115 .85746 .51685 .49518 .0659 .33382 61.78
T. S. Eliot .40272 .77498 .50522 .3029 .0097 .24015 84.46
Wally Lamb .43451 .43391 .4988 .41759 .39898 .35242 18.15
Jack London .46983 .58986 .49372 .37591 .22931 .34179 62.01
Nora Ephron
a
.41791 .44425 .48903 .50577 .43852 .42495 38.54
J. R. R. Tolkien .51727 .65036 .47838 .24915 .1212 .19578 88.10
Thomas Wolfe .38744 .43124 .46453 .45857 .31715 .3587 43.02
Maya Angelou .31693 .71394 .46106 .52677 .05937 .35462 65.74
Ray Bradbury
a
.42879 .63858 .43848 .47032 .13004 .40118 61.78
E. B. White
b
.26678 .58697 .398 .53034 .06789 .34382 58.56
Ernest Hemingway .34337 .48488 .35443 .42061 .28447 .42089 88.61
Margaret Mitchell .28367 .34438 .34239 .58292 .5762 .55295 33.59
Tony Hillerman .3357 .17358 .342 .61569 .75155 .60498 18.99
Jean M. Auel .31154 .20389 .31293 .53789 .68404 .5551 17.54
Herman Wouk .22863 .3145 .29553 .74091 .64477 .68206 24.26
Dick Francis .3337 .0736 .26984 .52968 .82677 .55476 17.96
Stephen King
b
.21384 .45346 .25586 .38103 .07571 .33493 91.88
James Clavell .17848 .17264 .227 .61487 .69139 .6067 22.95
Anne McCaffrey
b
.22414 .33623 .21998 .33587 .38763 .39377 20.48
Robert Ludlum .10754 .34051 .18886 .7557 .54263 .70228 38.77
James Michener .10763 .12698 .18051 .8169 .80242 .76172 35.83
Brian Herbert
b
.1684 .35992 .16544 .0515 .20884 .18096 04.01
Sue Grafton .15722 .18338 .15637 .73379 .68498 .72375 32.57
Jonathan Kellerman .10688 .0457 .0842 .73455 .89669 .76704 18.89
John Grisham .0222 .26695 .07328 .83026 .56548 .77815 74.38
Jackie Collins .0716 .0163 .0138 .80573 .79542 .77975 45.63
Judith Krantz .0353 .0674 .0175 .84554 .8607 .83127 37.37
Clive Cussler .0174 .14553 .0244 .76557 .69604 .79972 29.67
Tom Clancy .0382 .36129 .0358 .81911 .26612 .74479 80.77
Nelson DeMille .0996 .064 .0625 .71929 .81083 .73477 11.75
Sidney Sheldon .1303 .0986 .066 .80869 .91138 .81484 34.76
Danielle Steel .1226 .013 .1038 .88554 .76561 .87744 71.95
James Patterson .1355 .13095 .1048 .82102 .46758 .76554 54.50
Note. Factor loadings in bold type are significant based on the .40 or greater criterion.
a
Authors excluded because of loadings greater than .40 on both factors.
b
Authors excluded because of loadings less than .40 on both factors.
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5
DIFFERENT STORIES
factor. Two authors (Nora Ephron and Ray Bradbury) had loadings
of greater than 0.40 on both factors, and four authors (Brian
Herbert, Stephen King, Anne McCaffrey, and E.B. White) had
loadings of less than 0.40 on both factors. As these six (9.23%)
authors could not be clearly associated with either factor, they
were not included in the factor-based scores. As in the previous
analyses, the authors associated with the first factor could mostly
be easily categorized as literary while those linked to the second
factor could generally be classified as authors of genre fiction (see
Table 2). Based on the groups of authors generated by this final
factor analysis, recognition scores for literary and genre fiction
were created by calculating the proportion of authors participants
identified of each type.
As with any factor analysis, the factors must be interpreted. In
this case, we propose that the factors can be meaningfully inter-
preted as reflecting mostly literary and genre writers. There are
some notable exceptions. For example, Ernest Hemingway, an
acclaimed author and Nobel Prize winner, is included (barely) in
the genre factor, and Isaac Asimov, one of the most influential
science fiction writers, is included in the literary factor. We do not
believe these categorizations necessarily indicate that Hemingway
is actually a genre fiction author or that Asimov should not be
considered a science fiction writer. However, it is also true that
Asimov, and other genre authors included in the literary category
(i.e., Raymond Chandler, Jack London, and J. R. R. Tolkien),
challenged the formulas of their genres, giving their work literary
characteristics according to our theoretical view. Conversely, some
acclaimed writers were linked to the genre fiction category: Mar-
garet Mitchell (a National Book Award and Pulitzer Prize winner),
Ernest Hemingway (Nobel Prize winner), and Herman Wouk
(Pulitzer Prize winner). Both Herman Wouk and, especially, Mar-
garet Mitchell are known not only by readers but also by viewers
of popular screen adaptations of their works, perhaps contributing
to their inclusion in the original genre category. Moreover, Mitch-
ell’s novel, Gone with the Wind, follows many of the formulas of
romance fiction, and Wouk’s prize-winning The Caine Mutiny was
read by some critics of its day as upholding conventional ideas and
values (Swados, 1953). Their inclusion in the genre category is
therefore not inconsistent with our theoretical perspective. Thus,
despite a few ambiguous categorizations, the factors yielded by the
factor analysis generally distinguish between literary and genre
fiction. We revisit this matter and others related to characteristics
of the two factors in a series of additional analyses discussed after
presentation of the primary findings.
Predicting RMET performance. The hypothesis that famil-
iarity with literary fiction is positively associated with perfor-
mance on the RMET was tested separately in the two samples
using similar procedures: Recognition rates for the literary and
genre factors were entered as independent variables in a general
linear model (GLM; Proc GLM, SAS v9.2) with RMET perfor-
mance as the dependent variable. The number of foils (i.e., non-
authors) selected on the ART was included as a covariate follow-
ing conventional methods (e.g., Mar et al., 2006). Potentially
confounding demographic variables that independently related to
both RMET scores and one of the two measures of familiarity with
fiction were also included as covariates. Accordingly, age was
included as a covariate in analysis of the first sample (See Table 1).
In the first sample, there was a significant effect of college major
on RMET performance.
2
Likewise, undergraduate major was a
significant predictor exposure to both literary and genre fiction.
3
Consequently, undergraduate major was added as a covariate in the
analysis of the first sample. In both samples, female participants
performed better than males on the RMET,
4
and they were more
familiar with both literary fiction
5
and genre fiction.
6
In the second
sample, which was composed of datasets from prior experiments,
experimental condition (literary fiction vs. controls) was also in-
cluded as a covariate.
7
In the second sample, participants who had
attained at least a college degree performed better on the RMET
than those who had not.
8
They also recognized more literary
9
and
genre
10
authors. Consequently, level of education was also added
as a covariate.
For each analysis, cases with high leverage were identified using
Cook’s distance. Those with Cook’s distances greater than a conven-
tional criterion (4/n) were removed from the analysis (Chen, Ender,
Mitchell, & Wells, 2003). This led to exclusion of cases from both
analyses (4.26% in the first sample, 3.56% in the second). Given the
high correlation of the measures of familiarity with literary and genre
fiction, tolerance statistics were checked for each variable to confirm
that they were above the conventional threshold of .10. In both
samples, no variable had an associated tolerance statistic below .10
(Sample 1: all .29; Sample 2: all .44).
Results from the GLM conducted with the first sample indicated
that recognition rates of literary authors positively predicted
RMET performance, and age was negatively related to RMET
scores (see Table 3). Analysis of the second sample yielded sig-
nificant effects of familiarity with literary fiction and experimental
condition (see Table 4). Results from both samples therefore
support the hypothesis that familiarity with literary but not genre
fiction is positively associated with RMET performance. More-
2
The main effect of undergraduate major, F(4, 1238) 3.53, p.007,
p
2.011, 95% CI [.000, .002], was driven primarily by higher scores
among humanities majors (n394, M26.84, SD 3.84) than majors
in business (n173, M26.04, SD 3.82, t2.29, p.02), natural
sciences (n291, M26.24, SD 3.78, t2.04, p.04), and
participants who indicated “other” (n169, M25.62, SD 3.75, t
3.47, p.001). Majors in the social sciences (n173, M26.42, SD
3.77, t2.03, p.04) performed better than those who indicated “other.”
3
The effect of undergraduate major was significant on for both exposure
to literary fiction, F(4, 1238) 34.34, p.001, p
2.096, 95% CI [.068,
.129], and genre fiction, F(4, 1238) 8.60, p.001, p
2.027, 95% CI
[.010, .044].
4
Sample 1: M
Female
26.50, SD 3.86 vs. M
Male
25.96, SD 3.68;
F(1, 1241) 4.95, p.02, p
2.004, 95% CI [.000, .013]; Sample 2:
M
Female
25.95, SD 4.03 vs. M
Male
25.16, SD 4.68; F(1, 894)
7.33, p.006, p
2.008, 95% CI [.000, .023].
5
Sample 1: M
Female
.52, SD .27 vs. M
Male
.45, SD .26; F(1,
1241) 18.88, p.001, p
2.015, 95% CI [.004, .031]; Sample 2:
M
Female
.35, SD .24 vs. M
Male
.31, SD .22 F(1, 894) 6.76, p
.009, p
2.007, 95% CI [.000, .022].
6
Sample 1: M
Female
.47, SD .28 vs. M
Male
.37, SD .26; F(1,
1241) 33.09, p.001, p
2.026, 95% CI [.011, .045]; Sample 2:
M
Female
.37, SD .24 vs. M
Male
.27, SD .21; F(1, 894) 36.65,
p.001, p
2.039, 95% CI [.018, .067].
7
Detailed reports of the effects of the experimental conditions for four
of the six experiments are reported in Kidd and Castano (2013).
8
M
Degree
25.90, SD 4.47 vs. M
No degree
25.26, SD 4.23; F(1,
894) 4.64, p.031, p
2.005, 95% CI [.000, .018].
9
M
Degree
.397, SD .248 vs. M
No degree
.283, SD .205, F(1,
894) 56.39, p.001, p
2.059, 95% CI [.032, .091].
10
M
Degree
.362, SD .251 vs. M
No degree
.287, SD .218, F(1,
894) 22.75, p.001, p
2.024, 95% CI [.008, .048].
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6KIDD AND CASTANO
over, this effect could not be attributed to individual differences in
age, education, or gender.
Study 2
A second study was conducted to further test the central hy-
pothesis that familiarity with literary fiction would predict ToM
performance. A self-report measure of dispositional empathy was
included to help test the possibility that the relation between
exposure to literary fiction and ToM performance found in the first
two samples was attributable to individual differences in trait
empathy. That is, it may be that people who are more empathic are
both more likely to read fiction and to perform well on tests of
ToM because of an underlying interest in others. Although prior
research has demonstrated that individual differences in the Five
Factor personality dimensions and a tendency to become immersed
in fiction do not account for the relation between exposure to
fiction in general and ToM performance (Mar et al., 2009), this is
to our knowledge the first study to specifically examine whether
individual differences in multiple components of trait empathy
account for the relation.
Method
Participants (N307) were recruited using Amazon.com’s Me-
chanicalTurk service and were compensated $1.50 for their partici-
pation in the study, which was administered online using Qualtrics.
Only data from native English speakers were retained (N299).
Based on the smallest model effect size previously observed (p
2
.05) and the need to be able to detect a significant model after
including the three IRI subscales as covariates, about 300 participants
were needed to achieve power of .95 (Faul, Erdfelder, Buchner, &
Lang, 2009). Upon granting informed consent, participants completed
the RMET and ART as in the prior study.
Participants also completed measures of cognitive empathy (i.e.,
Perspective Taking [PT]), affective empathy (Empathic Concern
[EC]), and self-focused emotional reactivity (Personal Distress
[PD]) from the Interpersonal Reactivity Index (IRI, Davis, 1983),
a widely used self-report multidimensional measure of empathy.
The Fantasy subscale of the IRI, which assesses the tendency to
become immersed in fictional worlds, was not administered, as
prior research has already demonstrated that it does not account for
the relation between reading fiction and ToM (Mar et al., 2009).
Each component of empathy was assessed based on participants’
reported agreement with 7 statements on a scale ranging from 1
(strongly disagree)to9(strongly agree). Finally, participants were
asked to indicate their age, gender, highest level of attained edu-
cation, and undergraduate major.
Results
Scores on the RMET and measures of literary and genre fiction
exposure were calculated as in the previous study. As with the
previous samples, participants were excluded from analysis if their
score on the RMET was lower than expected by chance alone (n
6). Participants were also excluded if they selected either no
authors on the ART or if they selected more foils than actual
authors (n30), leaving a final sample of 263 participants
(55.89% female, 74.05% White, 52.47% college graduates, see
Table 5 for other sample characteristics).
A series of one-way ANOVAs showed that female participants
were more familiar with genre fiction than males (M.31, SD
.23 vs. M.25, SD .20; F(1, 261) 5.40, p.02, p
2.020,
95% CI [.000,.065]) and performed better on the RMET (M
22.58, SD 3.98 vs. M21.52, SD 4.20, F(1, 261) 4.36,
p.03, p
2.016, 95% CI [.000,.058]). Therefore, gender was
included as a covariate in the test of the effects of familiarity with
literary and genre fiction on RMET performance. Similarly, EC
was positively correlated with familiarity with genre fiction and
with performance on the RMET (see Table 5), so it was also
included as a covariate. Neither PT nor PD correlated with RMET
performance, so they were not included as covariates. When in-
cluded as covariates, neither approaches significance (ps.35),
and none of the other effects change in terms of significance. Age
was included as a covariate because it was positively correlated
with familiarity with literary and genre fiction as well as with
RMET scores (see Table 5). In contrast to findings from the first
sample, undergraduate major was not significantly related to
RMET performance, F(4, 257) 0.36, p.83. The hypothesis that
familiarity with literary fiction predicts ToM performance was tested
by regressing RMET scores on familiarity with literary fiction, famil-
iarity with genre fiction, gender, age, EC, and foils selected on the
ART. To correct for skew, both measures of fiction familiarity were
square root transformed (the same pattern of significant results
emerges without transformations). As in the prior study, cases were
excluded based on Cook’s distance (4.94%), and a test of collinearity
Table 4
Results of GLMs With RMET as Dependent Variable for Sample
2(N866)
Variable (SE)(df)Fpp
295% CI
Model (6, 854) 14.55 .001 .09 [.05, .13]
Literary-ART .223 (.048) (1, 854) 21.54 .001 .024 [.008, .048]
Genre-ART .056 (.047) (1, 854) 1.38 .241 .001 [.000, .011]
Gender .077 (.066) (1, 854) 1.34 .246 .001 [.000, .011]
Education .057 (.067) (1, 854) .72 .397 .000 [.000, .009]
Condition .221 (.067) (1, 854) 10.82 .001 .012 [.002, .031]
Foils .067 (.033) (1, 854) 4.06 .044 .004 [.000, .018]
Note. ART Author Recognition Test; RMET Reading the Mind in
the Eyes Test. Sample size reflects cases excluded on the basis of Cook’s
D. Gender coded as Female 1, Male 0. Education coded as No college
degree 0, College degree or higher 1. Condition coded as Literary
0, Comparison 1.
Table 3
Results of GLMs With RMET as Dependent Variable for Sample
1(N1,190)
Variable (SE)(df)Fpp
295% CI
Model (9, 1180) 7.03 .001 .05 [.02, .07]
Literary-ART .135 (.046) (1, 1180) 8.56 .003 .007 [.000, .019]
Genre-ART .002 (.052) (1, 1180) .00 .963 .000 [.000, .000]
Gender .106 (.064) (1, 1180) 2.71 .100 .002 [.000, .010]
Age .173 (.036) (1, 1180) 22.41 .001 .018 [.006, .036]
Foils .006 (.028) (1, 1180) .05 .831 .000 [.000, .003]
College major (4, 1180) 2.55 .037 .008 [.000, .018]
Note. ART Author Recognition Test; RMET Reading the Mind in
the Eyes Test. Sample size reflects cases excluded on the basis of Cook’s
D. Gender coded as Female 1, Male 0.
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7
DIFFERENT STORIES
revealed that all tolerance statistics were above the conventional
threshold of .10 (all .30). As expected, familiarity with literary
fiction predicted RMET performance, but familiarity with genre fic-
tion did not (see Table 6).
Supplementary Analyses
In the analyses reported above, we focus on scores based on the two
factors extracted in the factor analysis. Although we favor this em-
pirical approach to identifying patterns of exposure to fiction, we also
acknowledge that it is not without ambiguities. Based on reviews of
an earlier submission of this paper, we have conducted four additional
analyses to address alternate interpretations of the factors.
Edited literary and genre categories. Supplementary analy-
ses were conducted using literary and genre scores calculated after
removing authors that a reviewer proposed were improperly catego-
rized by the factor analysis. Specifically, four acclaimed authors
known for their work in specific genres were removed from the
literary category: Isaac Asimov, Raymond Chandler, Jack London,
and J.R.R. Tolkien. Three authors originally included in the genre
ART were also removed: Margaret Mitchell (a National Book Award
and Pulitzer Prize winner), Ernest Hemingway (Nobel Prize winner),
and Herman Wouk (Pulitzer Prize winner). The revised literary and
genre ART scores were entered as predictors of RMET performance
along with the covariates included in the primary analysis of each
sample. Removing these possibly incorrectly classified authors
(though see discussion of this above) does not alter the statistical
significance of any of the key statistical tests (see Table 7).
Equal numbers of literary and genre authors. The factor
analyses led to the identification of a literary factor with twice as
Table 7
Results of GLM With RMET as Dependent Variable and Revised
Literary and Genre ART Scores
Sample Literary Genre
1␤⫽.13, SE .04, p.001 ␤⫽⫺.00, SE .04, p.950
2␤⫽.21, SE .04, p.001 ␤⫽.06, SE .04, p.155
3␤⫽.20, SE .08, p.016 ␤⫽.10, SE .09, p.281
Note. RMET Reading the Mind in the Eyes Test; ART Author
Recognition Test. Covariates included in the primary analysis are included
in these models but are not reported.
Table 5
Sample Characteristics and Correlations Among Variables for Study 2
Variable Age
ART
(␣⫽.95) ART foils
Literary ART
(␣⫽.94)
Genre ART
(␣⫽.89)
RMET
(␣⫽.75)
EC
(␣⫽.88)
PT
(␣⫽.83)
PD
(␣⫽.86)
Total sample (N263) 33.76 (11.09)
[32.41, 35.11]
18.53 (13.68)
[16.87, 20.19]
.82 (2.63)
[.50, 1.14]
.29 (.22)
[.26, .32]
.28 (.22)
[.26, .31]
26.11 (5.01)
[25.50, 26.71]
6.43 (1.56)
[6.24, 6.62]
6.32 (1.31)
[6.16, 6.48]
4.17 (1.58)
[3.98, 4.36]
ART .37
ⴱⴱⴱ
[.26, .47] — ———
ART Foils .03 [.08, .15] .04 [.16, .07]
Literary ART .25
ⴱⴱⴱ
[.13, .36] .95
ⴱⴱⴱ
[.93, .96] .14
[.02, .26] ———
Genre ART .56
ⴱⴱⴱ
[.47, .64] .86
ⴱⴱⴱ
[.83, .89] .09 [.02, .21] .74
ⴱⴱⴱ
[.68, .79] ——
RMET .18
ⴱⴱⴱ
[.06, .29] .34
ⴱⴱⴱ
[.22, .44] .14
[.25, .02] .28
ⴱⴱⴱ
[.16, .38] .29
ⴱⴱⴱ
[.17, .39] ——
EC .23
ⴱⴱⴱ
[.11, .34] .10 [.01, .22] .05 [.17, .06] .06 [.18, .05] .15
[.03, .26] .20
ⴱⴱⴱ
[.08, .31] ——
PT .07 [.04, .19] .03 [.08, .15] .01 [.11, .13] .03 [.08, .15] .05 [.06, .17] .11 [.00, .23] .57
ⴱⴱⴱ
[.49, .65] ——
PD .11 [.22, .00] .09 [.21, .02] .04 [.16, .07] .07 [.19, .04] .14
[.26, .02] .07 [.19, .04] .05 [.06, .17] .06 [.18, .05]
Note. ART Author Recognition Test; RMET Reading the Mind in the Eyes Test; EC Empathic Concern; PT Perspective Taking; PD Personal Distress. Literary ART and Genre ART
scores are calculated as proportions of authors recognized. Standard deviations for each mean are reported in parentheses. 95% Confidence intervals for each mean and correlation coefficient are reported
in brackets.
Correlation significant at p.05.
ⴱⴱⴱ
Correlation significant at p.001.
Table 6
Results of GLM With RMET as Dependent Variable for Study 2
(N 245)
Variable (SE)(df)Fpp
295% CI
Model (6, 238) 8.50 .001 .17 [.08, .24]
Literary-ART .222 (.093) (1, 238) 5.64 .018 .021 [.000, .071]
Genre-ART .126 (.108) (1, 238) 1.37 .243 .013 [.000, .038]
Gender .225 (.122) (1, 238) 3.38 .067 .002 [.000, .055]
Age .040 (.074) (1, 238) .29 .591 .003 [.000, .024]
EC .101 (.062) (1, 238) 2.62 .106 .001 [.000, .049]
Foils .125 (.060) (1, 238) 4.38 .037 .011 [.000, .063]
Note. ART Author Recognition Test; RMET Reading the Mind in
the Eyes Test; EC Empathic Concern; PT Perspective Taking; PD
Personal Distress. Sample size reflects cases excluded on the basis of
Cook’s D. Gender coded as Female 1, Male 0.
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8KIDD AND CASTANO
many authors as the genre factor. To test whether the different
effects of exposure to literary and genre fiction were a mere
artifact of this imbalance, supplementary analyses were conducted
in which literary exposure scores were calculated using only the
first 20 literary authors (as they appear in the ART as presented by
Acheson et al., 2008). Because the order of the authors in the ART
is completely arbitrary, the first 20 constitute a random subsample.
Across the three samples, there were no changes in the significance
of the relations reported below. Consequently, the relative effects
of exposure to literary and genre fiction on RMET performance
cannot be clearly attributed to the greater number of authors
composing the literary exposure measure (see Table 8).
Accounting for publication dates. A reviewer noted that
many of the genre authors have published their works more re-
cently than the literary authors, meaning that they are perhaps less
likely to be read in academic settings. If so, the literary scores may
actually reflect encounters with fiction in classrooms. To address
this potential confound, we created a variable to reflect the average
most recent year of publication of each recognized author. For
example, James Joyce’s most recent novel, Finnegans Wake, was
first published in 1939, and Tom Clancy’s most recent novel,
Command Authority, was published in 2013. A participant who
recognized only those two authors would have a value for this new
variable of 1,976.5. Thus, readers of primarily older, and perhaps
more canonical, authors would have lower scores on this variable than
readers of mostly contemporary authors. Therefore, if the effect of
literary familiarity is driven by the older age of works by the literary
authors, accounting for the average publication date should eliminate
or significantly attenuate it. This variable was added as a covariate to
the analyses reported in the main text for all three samples. The results
indicate that adding the average publication date covariate does not
alter the effect of literary fiction in any of the three samples, either in
terms of significance or the magnitude of the standardized regression
coefficient (see Table 9).
Analysis of specific genres. Given past research indicating
different effects of specific types of genre fiction (Fong et al.,
2013), we consulted each author’s Wikipedia page was consulted
to determine whether the author was clearly linked to a particular
genre. Of the authors categorized as literary in the factor analysis,
only Isaac Asimov, Raymond Chandler, and J.R.R. Tolkien were
associated on Wikipedia with genres (science fiction, crime, and
fantasy, respectively). Of the authors categorized as genre authors
in the factor analysis, six authors were classified as romance
writers: Jackie Collins, Judith Krantz, Margaret Mitchell, James
Patterson, Sidney Sheldon, and Danielle Steel. Nine authors were
classified as crime, thriller, mystery, adventure, or detective writ-
ers (for brevity, this category will be subsequently referred to as
the thriller/mystery category): Tom Clancy, Clive Cussler, Dick
Francis, Sue Grafton, John Grisham, Tony Hillerman, Jonathan
Kellerman, Robert Ludlum, and Nelson DeMille. Three were
categorized as writers of historical fiction: James Clavell, James
Michener, and Herman Wouk. Jean M. Auel was classified as a
fantasy writer.
Based on these classifications, two new genre fiction scores were
created to reflect recognition rates for the categories of romance
fiction and thriller/mystery. Participants across the studies recognized,
on average, more than two of the authors in each of the categories.
These numbers are comparable with those reported in previous studies
of specific genres (e.g., Fong et al., 2013). Consequently, additional
analyses were conducted using recognition rates of literary, romance,
and thriller/mystery authors as predictors of RMET performance.
Neither of these two measures of familiarity with specific types of
genre fiction significantly predicted RMET performance, and the
effect of literary fiction familiarity remained significant (see Table
10). Given that these measures of familiarity with romance and
mystery/thriller fiction are completely post hoc, are not supported by
the factor analyses, and have not been otherwise validated, we urge
caution in interpreting these null effects.
Comparison of recognition rates. A reviewer proposed the
literary authors are not as easy to recognize as the genre authors.
If so, recognition of those authors may be a more reliable indicator
of actual reading habits, regardless of the type of fiction read.
However, a comparison of the recognition rates of authors in each
category (see Table 2) revealed that recognition rates for literary
authors (43.65%, SD 22.51) did not significantly differ from
those for genre authors (39.54%, SD 22.86; F(1, 58) 0.44,
p.516).
General Discussion
Time spent reading fiction may sharpen our capacity to success-
fully understand others, as studies over the past decade suggest (Mar
et al., 2006, 2009). The research findings we present here go one step
further, providing evidence that it is specifically engagement with
literary fiction that positively predicts theory of mind (ToM) perfor-
mance. In three independent and large samples, it was found that
familiarity with authors of literary, but not authors of genre fiction,
predicted participants’ performance on the RMET, a well-validated
and widely used measure of ToM.
Importantly, despite the differences between the recruitment and
consequent makeup of the samples, and the different methods used
with the three samples, the results are consistent. Unique methodolog-
ical features of each study are thus unlikely to explain the reported
results. For example, the first sample was recruited via a link embed-
ded in an article about the effects of reading literary fiction on ToM,
raising the possibility that participants may have been aware of the
hypothesis. However, for this to have affected results, participants
would have needed to agree with our hypothesis, be aware of how
well they were doing on the RMET, and understand that some of the
authors on the ART would be classified as literary and others as genre.
That most or many of the participants in the first sample would have
responded in this way seems implausible. Likewise, participants in the
second sample were recruited to participate in experiments, and ex-
perimental condition was included as a covariate in order to rule it out
Table 8
Results of GLMs With RMET as Dependent Variable and
Literary and Genre ART Scores Reflecting Equal Numbers
of Authors
Sample Literary (first 20) Genre
1␤⫽.14, SE .04, p.001 ␤⫽⫺.00, SE .05, p.895
2␤⫽.23, SE .04, p.001 ␤⫽.05, SE .04, p.225
3␤⫽.26, SE .08, p.001 ␤⫽.05, SE .09, p.561
Note. RMET Reading the Mind in the Eyes Test; ART Author
Recognition Test. Covariates included in the primary analysis are included
in these models but are not reported.
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.
9
DIFFERENT STORIES
as a potential confound. More generally, the consistency of the effects
across the three samples shows that they are robust and cannot be
attributed to one particular sample or method.
Although nearly all fiction may provide a basis for simulated social
experiences (Koopman & Hakemulder, 2015; Mar & Oatley, 2008),
the present findings suggest that literary fiction is most likely to
prompt readers to rely extensively on ToM, leading them to more
fully recruit ToM-related processes, even beyond the immediate con-
text of reading. This finding is consistent with prior research demon-
strating short-term benefits to ToM performance caused by reading
short works of literary fiction (Black & Barnes, 2015a; Kidd &
Castano, 2013). We propose that these findings emerge because the
implied (rather than explicit) sociocognitive complexity, or roundness
of characters, in literary fiction prompts readers to make, adjust, and
consider multiple interpretations of characters’ mental states (Zun-
shine, 2015). Though both prior experimental findings and the current
results are consistent with this view, no direct evidence speaks to the
precise mechanisms through which literary fiction affects ToM. Fu-
ture research either focusing on the linguistic, syntactic, and other
characteristics of literary texts, or that creates ad hoc texts that vary
along specific dimensions, will provide valuable information about
such mechanisms.
Before turning to what we see as important implications of the
present findings, let us briefly discuss issues that are inherent in the
correlational character of the present studies. First, one obvious ques-
tion is about the possible roles of third variables in the emergence of
the relationship between familiarity with literary fiction and ToM
performance. Across the three independent samples, this relationship
could not be explained by demographic characteristics such as age,
gender, or educational attainment. In the first and third samples,
undergraduate major was also ruled out as an explanation for the
results. This point is particularly important given research linking
individual differences in RMET performance to the decision to
choose a major in the humanities (Billington, Baron-Cohen, &
Wheelwright, 2007).
11
Individual differences in personality also seem
unable to explain the present effects. Though evidence suggests that
readers of different types of fiction (e.g., literary, thriller, romance)
differ in certain Big Five personality traits (Kraaykamp & Van Eijk,
2005; Michelson, 2014), these personality traits are not clearly related
to RMET performance (Ferguson & Austin, 2010; Nettle & Liddle,
2008). Moreover, prior research has demonstrated that individual
differences in personality do not account for the relation between a
global measure of exposure to fiction and performance on the RMET
(Mar et al., 2009), and self-reported empathic concern did not affect
the relation between familiarity with literary fiction and ToM in our
second study. Consequently, it does not appear that an obvious third
variable can account for the present results.
In the three samples, genre fiction was not uniquely related to
RMET performance after accounting for familiarity with literary
fiction. This may appear inconsistent with prior findings of a positive
relation between familiarity with romance fiction (but not science
fiction/fantasy or suspense/thriller) and RMET performance (Fong et
al., 2013). A direct comparison, however, is difficult. The present
study included no a priori measure of familiarity with romance fiction,
and Fong et al. (2013) did not measure exposure to literary fiction.
Furthermore, the genre category in the present study included only six
romance writers, limiting our ability to reliably test the effects of this
specific genre. Nonetheless, our own and Fong et al.’s (2013) research
converge on the point that the extent to which fiction draws attention
to characters’ thoughts, feelings, and relationships likely underlies its
impacts on ToM, a point underscored by recent neuroimaging re-
search (Tamir, Bricker, Dodell-Feder, & Mitchell, 2016). As dis-
cussed above, however, how attention is drawn probably makes an
important difference (Zunshine, 2015).
The present research speaks to both psychological and literary
theory. A growing body of research addressing the behavioral (e.g.,
Declerck & Bogaert, 2008; Engel et al., 2014), personality (e.g.,
Ferguson & Austin, 2010; Nettle & Liddle, 2008), and demographic
(e.g., Kraus et al., 2010; Sherman, Lerner, Renshon, Ma-Kellams, &
Joel, 2015) correlates of ToM in normal adult populations suggests
that ToM is not an all-or-nothing developmental achievement, but is
recruited to different degrees (and with varying success) across indi-
viduals and situations. The present findings provide important evi-
dence of how this fundamental human capacity might be moderated
by specific cultural practices (Heyes & Frith, 2014). Instead of being
interpreted as evidence of the superiority of literary fiction over genre
fiction, the present findings point to the possibility that these different
cultural artifacts have distinct influences on the process of social
perception and on how we navigate the social world. The understand-
ing of others in terms of their mental states, that is, engaging in ToM
processes, is only one strategy for social navigation. Just as important,
although potentially problematic as extensive research on category-
based perception has shown (Swencionis & Fiske, 2014), is our
understanding of others in terms of their social identities and roles
(Hirschfeld, 2006). We speculate that genre fiction, with more stereo-
typical or stock characters, may boost this other strategy of social
perception, instead of drawing attention to the idiosyncratic, subjec-
tive experiences of others.
Beyond their relations to psychological theory and research, these
findings have implications for the study and teaching of literature. The
primary finding that exposure to literary fiction positively predicts
RMET performance across these broad samples is consistent with the
theoretical expectation that literary fiction affords greater opportuni-
ties for engaging with characters in a manner that promotes attention
11
We thank an anonymous reviewer for drawing our attention to this
research.
Table 9
Results of GLMs Predicting RMET With Average Publication Year as a Covariate
Sample Literary Genre Average year
1␤⫽.13, SE .04, p.003 ␤⫽.02, SE .05, p.597 ␤⫽⫺.04, SE .03, p.194
2␤⫽.22, SE .04, p.001 ␤⫽.03, SE .05, p.559 ␤⫽.00, SE .00, p.300
3␤⫽.23, SE .09, p.014 ␤⫽.12, SE .11, p.270 ␤⫽⫺.09, SE .06, p.156
Note. RMET Reading the Mind in the Eyes Test. Covariates included in the primary analysis are included
in these models but are not reported.
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10 KIDD AND CASTANO
to their nuances and complexities (Culpeper, 2001; Hakemulder,
2000; Miesen, 2004). Second, these results suggest that fiction should
not be understood as a monolithic construct when it comes to appre-
ciating its potential effects on psychological processes (Koopman &
Hakemulder, 2015). Rather, different types of fiction may foster
different types of social cognition processes; some require that readers
rely more on ToM, whereas others demand greater reference to a fine
understanding of social identities and social roles.
In this regard, it should be noted that the very category of literary
fiction as understood in our own and related research, is a socially
constructed category that is culturally (Western) and historically
(modern) bounded. The focus on psychologically complex round
characters, which is considered a hallmark of literary fiction, reflects
a specific cultural and historical understanding of what is valuable and
important: the individual. Needless to say, it was not always so. What
is associated with literariness in contemporary American culture was
considered an undesirable marker of bourgeois decadence by mid-
20th century proponents of Socialist Realism. In other cultural and
historical periods or settings, fiction that is more oriented toward the
transmission of norms or depicting archetypal flat characters may
stand higher in the hierarchy of genres (Eder et al., 2010). This kind
of fiction, as speculated above, may foster Theory of Society socio-
cognitive processes, rather than ToM processes.
Just as reading critically acclaimed fiction is theorized to promote
ToM insofar as it draws attention to others’ subjective experiences, it
seems likely that other cultural practices may affect ToM in the same
way. Biographies, memoirs, and narrative journalism are forms of
nonfiction that could have the same effect (Tamir et al., 2016), and
recent research shows that playing a nonviolent narrative video game
(Bormann & Greitemeyer, 2015) or watching acclaimed TV dramas
(Black & Barnes, 2015b) also improves ToM. Moreover, social
environments that provide greater opportunities for interactions that
are not rigidly based on social identities and roles may also foster
ToM development. For example, a conversation among new members
of a civic or religious organization would be more likely to prompt its
participants to rely on ToM than a scripted telemarketing call. The
influence of these practices notwithstanding, it is possible that the
effects of literary fiction may be especially apparent because it allows
readers to reflect upon the behavior and mental states of characters at
their own pace and with virtually none of the risks (perceived or real)
associated with real world social behavior.
The findings and rationale presented here support a model of
cultural engagement that includes reciprocal relations of minds and
culture. Art that elicits culturally valued psychological processes may
be more likely to be produced and endorsed by critics. Supported by
engagement with such art, those psychological processes may in turn
become more efficient and valued. This view is consistent with recent
advances in psychological theories of culture that posit that “repeated
and continuous engagement in some select set of practices involving
certain features . . . may lead to some characteristic patterns of psy-
chological response” (Markus & Kitayama, 2010, p. 427). In this way,
the creative works that are especially admired may express and cause
differences in how people across communities perceive their real
social worlds. This theory also aligns with sociological approaches to
understanding the emergence and transmission of culture, such as
Bourdieu’s concept of habitus (Bourdieu, 1989; Lizardo, 2004),
which emphasizes the importance of sociocultural affordances in
shaping patterns of perception and thought. As psychological research
more specifically addresses the impacts of cultural products, practices,
and institutions, it may become more relevant to traditionally sociolog-
ical questions regarding the emergence and transmission of culture.
Alongside existing results, those presented here also raise interest-
ing theoretical and empirical questions about the broader cultural
impacts of fiction. For example, research suggests both a positive
relation between reading fiction and SES (National Endowment for
the Arts, 2013; Notten et al., 2015), and a negative relation between
SES and ToM (e.g., Kraus et al., 2010; Sherman et al., 2015). It seems
possible that the experience of deep intersubjectivity afforded by
literary fiction (which is often seen as high status) may counteract the
feelings of social dominance (Sherman et al., 2015) and independence
(Kraus et al., 2010) that are thought to lie at the root of the negative
relation between SES and ToM. For the same reason, reading literary
fiction may also help to improve ToM among individuals who strug-
gle with interpersonal relationships, such as those with subclinical but
high levels of narcissistic self-focus (Hepper, Hart, & Sedikides,
2014; Vonk, Zeigler-Hill, Mayhew, & Mercer, 2013). Future research
may help to better reveal the social and individual effects of cultivat-
ing literary fiction and its readers.
The finding that familiarity with literary fiction is positively related
to performance on an advanced test of ToM helps to refine under-
standing of variability in ToM among normal adults while addressing
theoretical and pedagogical questions in the humanities. More
broadly, this research reflects a concrete approach to studying engage-
ment with cultural products that will contribute to psychologists’
knowledge of cultural sources of variability in important capacities or
personality dimensions. It may also contribute to a more informed
Table 10
Results of GLMs Predicting RMET Performance With Specific Genres
Sample Literary Romance Mystery/Thriller
1␤⫽.14, SE .04, p.001 ␤⫽.02, SE .04, p.578 ␤⫽⫺.02, SE .04, p.550
M3.12, SD 2.032 M3.59, SD 2.56
95% CI [3.00, 3.23] 95% CI [3.45, 3.74]
2␤⫽.22, SE .04, p.001 ␤⫽.04, SE .05, p.392 ␤⫽.02, SE .05, p.678
M2.31, SD 1.88 M2.76, SD 2.14
95% CI [2.18, 2.44] 95% CI [2.62, 2.90]
3␤⫽.26, SE .08, p.002 ␤⫽.09, SE .09, p.294 ␤⫽⫺.01, SE .09, p.899
M2.22, SD 1.82 M2.34, SD 2.07
95% CI [2.00, 2.44] 95% CI [2.09, 2.59]
Note. RMET Reading the Mind in the Eyes Test. Means and standard deviations in the Romance and
Mystery/Thriller columns reflect the average number of authors identified. Covariates included in the primary
analysis are included in these models but are not reported.
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.
11
DIFFERENT STORIES
society in which individuals are equipped to better understand how
their engagement with fiction affects their experiences of the real
world.
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Received January 20, 2016
Revision received March 15, 2016
Accepted April 26, 2016
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DIFFERENT STORIES
... That is, gaps in the story and the mental states of the characters are meaningfully implemented, inviting the reader to engage with the story and its deeper meaning more thoroughly, being related to the concept of foregrounding (Miall & Kuiken, 1999). Additionally, inferences about mental states of round characters are more effortful because these characters are more complex and less predictable than flat characters, whose predominant role is to further the storyline (Kidd & Castano, 2017. As these features contribute to the literariness of narratives, it seems reasonable to assume that reading of literary fiction (and less so genre fiction) may offer a better opportunity to improve social-cognitive abilities than reading genre fiction does. ...
... Supporting this assumption, Kidd and Castano (2017) found positive correlations between exposure to highbrow literature and readers' theory-of-mind performance across several samples, but not between exposure to genre literature and theory of mind. Recently, this pattern of results was replicated and extended to moral judgements (Kidd & Castano, 2019). ...
... This finding is consistent with the idea that literary fiction might be more suitable to cause self-reflective processes and personality change than popular fiction (Djikic et al., 2012;Koopman & Hakemulder, 2015). In particular, higher numbers of foregrounded features that deautomize readers' perception (Miall & Kuiken, 1994) as well as "round" characters, who better reflect the complexity of within-person and between-person processes (Kidd & Castano, 2017), might contribute to these differences in the perception of literary and popular stories. ...
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Reading literary fiction might be more beneficial for fostering social-cognitive skills (i.e., theory of mind and empathy) than reading popular fiction. However, the superiority of literary fiction might be complex and depend on readers’ narrative engagement and identification. To answer this research question, we conducted an experiment, in which 262 adult participants read either a literary story or a popular story. Afterwards participants’ perception of the story (literary quality, stimulation of reflection, influence on own life and attitudes), their narrative engagement, transportation and identification, as well as their theory-of-mind performance and self-reported empathy were assessed. We found that readers judged literary fiction to be of higher quality, to stimulate more (self-)reflection, to be of higher relevance to their lives, and to be more narratively engaging than popular fiction. Although literary and popular stories did not affect self-reported empathy and theory-of-mind performance differentially, readers’ narrative engagement, transportation, and identification moderated the effect of story condition on theory of mind. Readers of literary stories who were strongly transported into the stories and who strongly identified with its characters showed a better theory-of-mind performance than readers of popular stories. Our findings underline the importance of narrative processes for understanding social-cognitive story effects.
... A livello mentale, l'accuratezza è misurata solitamente attraverso i test di Teoria della mente, le cui prestazioni hanno dimostrato di essere potenziate dall'esposizione alla narrativa letteraria (Kidd, Castano, 2019;Black, Barnes, 2015;Kidd, Castano, 2017a;Kidd, Castano, 2017b;Kidd, Castano, 2018;Pino, Mazza, 2016;van Kuijk et al., 2018). A livello sociale, un indicatore di accuratezza sociale può essere ottenuto attraverso lo stesso paradigma usato per indagare gli effetti di falso consenso, guardando la correlazione tra le popolarità osservate e quelle stimate (de la Haye, 2000). ...
... Versioni modificate dell'ART sono state usate per distinguere i tassi di lettura di saggistica e narrativa (per esempio, e Mar, Oatley, Peterson 2009), così come i diversi generi di narrativa (per esempio, Fong, Mullin, Mar, 2013;Fong, Mullin, Mar, 2015). Come in studi precedenti (Kidd, Castano, 2019;Kidd, Castano, 2017a;vedi anche Moore, Gordon, 2015), qui abbiamo calcolato due punteggi principali basati sulle risposte dei partecipanti all'ART: proporzioni di autori letterari identificati correttamente (Literary: M = .29; SD = .22) ...
... Data la natura correlazionale dei dati, abbiamo cercato di escludere l'effetto di potenziali correlati dell'esposizione ai tipi di fiction. Il livello di istruzione è un probabile candidato, poiché l'esposizione alla stampa e le capacità di lettura di lingua e comprensione sono moderate dagli anni di istruzione e, in particolare, l'istruzione è stata trovata associata ai punteggi della variabile Mind Accuracy (RMET) e dell'ART (Kidd, Castano, 2017a). L'istruzione correlava con l'esposizione alla narrativa letteraria (r = .29, ...
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... In a review, most studies showed a positive relationship between arts engagement, empathy, and prosocial behaviour (125), although associations differed according to art and engagement type, population, and study design. For example, a range of moderately sized to large experimental studies in adults have found that mindful dancing can increase compassion (126), listening to music from other cultures can increase theory of mind and reduce prejudice against other groups (127), and increased reading of some (but not all) types of fiction can enhance theory of mind and mentalising (128). A review found that engaging in "behavioural synchrony" (doing an action in time with others), such as in music or dance, can improve theory of mind, with most evidence from studies in children (129). ...
... In such studies, reading and discussing texts is seen to create and extend social connections between people, thus reducing loneliness for instance. Other research suggests that reading narrative fiction can improve adults' emotional skills of empathy, perspective taking and mentalising [76,77]. Additionally, that the complex characters and stories offered by literary fiction (rather than those found in popular fiction) serve to augment the reader's empathetic understanding of others' mental states through fictional simulation, e.g., [78]. ...
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Hakemulder 2000) comes close to a concise summary of the research and theory. Being absorbed in a narrative can stimulate empathic imagination. Readers go along with the author/narrator in a (fictional) thought-experiment, imagining how it would be to be in the shoes of a particular character, with certain motives, under certain circumstances, meeting with certain events. That would explain why narrativity can result in a broadening of readers’ consciousness, in particular so that it encompasses fellow human beings. Fictionality might stimulate readers to consider the narrative they read as a thought experiment, creating distance between them and the events, allowing them to experiment more freely with taking the position of a character different from themselves, also in moral respects. Literary features, like gaps and ambiguous characterization, may stimulate readers to make more mental inferences, thus training their theory of mind. However, apart from literature possibly being able to train basic cognitive ability, we have little indication for the importance of Regarding self-reflection, while there is no convincing evidence that literary texts are generally more thought-provoking than non-literary texts (either narrative or expository), there is tentative indication for a relation between reading literary texts and self-reflection. However, as was the case for the studies on empathy, there is a lack of systematic comparisons between literary narratives and non-literary narratives. There are some suggestions regarding the processes that can lead to self-reflection. Empirical and theoretical work indicates that the combination of experiencing narrative and aesthetic emotions tends to trigger self-reflection. Personal and reading experience may influence narrative and aesthetic emotions. By proposing a multi-factor model of literary reading, we hope to give an impulse to current reader response research, which too often conflates narrativity, fictionality and literariness. The multi-factor model of literary reading contains (our simplified versions of) two theoretical positions within the field of reader response studies on underlying processes that lead to empathy and reflection: the idea of reading literature as a form of role-taking proposed by Oatley (e. g., 1994; 1999) and the idea of defamiliarization through deviating textual and narrative features proposed by Miall and Kuiken (1994; 1999). We argue that these positions are in fact complementary. While the role-taking concept seems most adequate to explain empathic responses, the defamiliarization concept seems most adequate in explaining reflective responses. The discussion of these two theoretical explanations leads to the construction of a theoret­ical framework (and model) that offers useful suggestions which texts could be considered to have which effects on empathy and reflection. In our multi-factor model of literary reading, an important addition to the previously mentioned theories is the concept »stillness«. We borrow this term from the Canadian author Yann Martel (2009), who suggests reading certain literary texts will help to stimulate self-contemplation (and appreciation for art), moments that are especially valuable in times that life seems to be racing by, and we are enveloped by work and a multitude of other activities. Other literary authors have proposed similar ideas. Stillness is related to, or overlaps with the more commonly used term »aesthetic distance«, an attitude of detachment, allowing for contemplation to take place (cf. Cupchik 2001). Stillness, we propose, allows a space in which slow thinking (Kahneman 2011) can take place. Stillness is not reflection itself, but a precondition for reflection. In our model, stillness is an empty space or time that is created as a result of reading processes: the slowing down of readers’ perceptions of the fictional world, caused by defamiliarization. Our multi-factor model suggests that while role-taking can take place for all types of narratives, literary and fictional narratives may evoke the type of aesthetic distance (stillness) that leads to a suspension of judgment, adding to a stronger experience of role-taking and narrative empathy.
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Past research on video game effects was often limited to explaining effects of game content and mode, leaving structural and contextual game elements scarcely investigated. The present research examined the yet unclear role of narration in video games, by adapting concepts and methodology from video game research based on self-determination theory as well as past research on the effects of literary fiction. Results provided evidence for the facilitation of immersion and an immersion-mediated enhancement of autonomy and relatedness need satisfaction through in-game storytelling, suggesting a mutual enhancement of immersion and need satisfaction. Moreover, in-game storytelling enhanced affective theory of mind. Perspectives on future research, connecting in-game storytelling and game content to complement current knowledge of video game effects on various real-world outcomes, are discussed.
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Socio-cognitive skills are crucial for successful interpersonal interactions. Two particularly important socio-cognitive processes are emotion perception (EP) and theory of mind (ToM), but agreement is lacking on terminology and conceptual links between these constructs. Here we seek to clarify the relationship between the two at multiple levels, from concept to neuroanatomy. EP is often regarded as a low-level perceptual process necessary to decode affective cues, while ToM is usually seen as a higher-level cognitive process involving mental state deduction. In information processing models, EP tends to precede ToM. At the neuroanatomical level, lesion study data suggest that EP and ToM are both right-hemispheres based, but there is also evidence that ToM requires temporal-cingulate networks, whereas EP requires partially separable regions linked to distinct emotions. Common regions identified in fMRI studies of EP and ToM have included medial prefrontal cortex and temporal lobe areas, but differences emerge depending on the perceptual, cognitive and emotional demands of the EP and ToM tasks. For the future, clarity of definition of EP and ToM will be paramount to produce distinct task manipulations and inform models of socio-cognitive processing. Copyright © 2015. Published by Elsevier Ltd.