In the Mood to Get Over Yourself: Mood Affects Theory-of-Mind Use

Abstract

Understanding others' behavior often involves attributing mental states to them by using one's "theory of mind." We argue that using theory of mind to recognize differences between one's own perspective and another's perspective is a deliberate process of inference that may be influenced by incidental mood. Because sadness is associated with more systematic and deliberate processing whereas happiness is associated with more heuristic processing, we predicted that theory-of-mind use would be facilitated by sadness compared with happiness. Two experiments supported this prediction, demonstrating that participants were more likely to utilize knowledge about others to make inferences about their mental states when they were induced to feel sad than when they were induced to feel happy. These results provide both theoretical insight into the psychological mechanisms that govern theory of mind as well as practical insight into a common source of variability in its use.

Full text

In the Mood to Get Over Yourself: Mood Affects Theory-of-Mind Use
Benjamin A. Converse, Shuhong Lin, Boaz Keysar, and Nicholas Epley
University of Chicago
Understanding others’ behavior often involves attributing mental states to them by using one’s “theory
of mind.” We argue that using theory of mind to recognize differences between one’s own perspective
and another’s perspective is a deliberate process of inference that may be influenced by incidental mood.
Because sadness is associated with more systematic and deliberate processing whereas happiness is
associated with more heuristic processing, we predicted that theory-of-mind use would be facilitated by
sadness compared with happiness. Two experiments supported this prediction, demonstrating that
participants were more likely to utilize knowledge about others to make inferences about their mental
states when they were induced to feel sad than when they were induced to feel happy. These results
provide both theoretical insight into the psychological mechanisms that govern theory of mind as well as
practical insight into a common source of variability in its use.
Keywords: egocentrism, theory of mind, perspective-taking, mood, heuristics
Reasoning about others’ mental states is an inescapable feature
of everyday life. An ambiguous joke following a manuscript
rejection can leave one wondering whether a colleague meant to be
light hearted or vindictive. A date’s raised eyebrows can leave one
wondering whether a new outfit is shockingly attractive or just
shocking. Such mental state inferences occur across a wide spec-
trum of affective experiences. Dejected academics and giddy ro-
mantics alike infer the mental states of their colleagues and com-
panions. Being emotional does not excuse one from making
inferences about other minds. We argue that it does, however, alter
how people make these inferences.
Theory of Mind and Mental Effort
Attributing beliefs, desires, and intentions to others requires
distinguishing between one’s own and others’ mental states. To do
so, one must construct a representation of another’s mental states
that avoids relying on unshared, egocentric knowledge. Such
theory-of-mind use is pervasive and often efficient, prompting
scholars to suggest that it is governed by a universal mental
module (Fodor, 1985; Friedman & Leslie, 2004; Sperber & Wil-
son, 2002; cf., Apperly, Samson, & Humphreys, 2005) that allows
for rapid and automatic reasoning about other minds without
effortful attention (Stone, Baron-Cohen, & Knight, 1998).
Experimental evidence, however, calls this automaticity hypoth-
esis into question. For instance, people respond slower to questions
that require theory-of-mind use than to questions that do not
(Apperly, Riggs, Simpson, Samson, & Chiavarino, 2006), and use
knowledge about others’ beliefs to understand spoken communi-
cation only after adjusting an initial egocentric interpretation (Ep-
ley, Morewedge, & Keysar, 2004; Keysar & Barr, 2002). Conse-
quently, people who are distracted or asked to respond quickly are
less likely to use what they know about others to make mental state
inferences (Epley, Keysar, Van Boven, & Gilovich, 2004; Lin,
Keysar, & Epley, 2008).
The apparent resource dependence of reconciling one’s own
perspective with another’s perspective is inconsistent with purely
automatic accounts of belief reasoning.
1
It suggests instead that
constructing inferences about others’ mental states requires effort-
ful reasoning to inhibit and correct an initial, often egocentric,
default (Epley, Keysar, et al., 2004; Keysar & Barr, 2002). This is
consistent with various dual-process accounts of judgment in
which an automatic default inference must be overcome by delib-
erate processing (e.g., Chaiken & Trope, 1999; Kahneman, 2003;
Sloman, 1996).
Mood and Cognitive Processing
Incidental mood could provide insight into the psychological
mechanisms that govern theory-of-mind use. Research demon-
strates that happiness diminishes the likelihood of engaging in
deliberate processing (e.g., Bless & Igou, 2005; Bodenhausen,
Mussweiler, Gabriel, & Moreno, 2001; Forgas, 1995), and hinders
executive control (Oaksford, Morris, Grainger, & Williams, 1996;
Phillips, Bull, Adams, & Fraser, 2002). If employing one’s theory
of mind requires deliberate processing, then happy people should
1
Although automaticity is a central component of modularity, demon
-
strations of deliberate components of theory-of-mind use do not preclude
all modular accounts. Some specify a two-step process that is not neces-
sarily inconsistent with our proposal (e.g., Friedman & Leslie, 2004).
Benjamin A. Converse and Nicholas Epley, Graduate School of Busi-
ness, University of Chicago; Shuhong Lin and Boaz Keysar, Department of
Psychology, University of Chicago.
This research was supported by NIH R01 Grant MH49685– 06A1 and
NSF Grant SES0241544. We thank Annie Huang, Megan Kolasinski,
Robin Lassonde, Regina Lewandoski, and Entzu Lin for help conducting
the experiments; Erica Kees and Ashley Swanson for help preparing the
movie clips; and Travis Carter for help with eye-tracking data analysis.
Correspondence concerning this article should be addressed to Benjamin
A. Converse, University of Chicago Graduate School of Business, Center
for Decision Research, 5807 South Woodlawn Avenue, Chicago, IL 60637.
E-mail: bconvers@chicagogsb.edu
Emotion Copyright 2008 by the American Psychological Association
2008, Vol. 8, No. 5, 725–730 1528-3542/08/$12.00 DOI: 10.1037/a0013283
725

employ their theory of mind less than should sad people. That is,
happy people should be less likely to use what they know about
others’ beliefs to make mental-state inferences. Such mood effects
would be inconsistent with a purely automatic account of theory-
of-mind use, but would be consistent with dual-process accounts of
theory-of-mind use.
Experiment 1
One hallmark of a developed theory of mind is the ability to
distinguish between what one knows and what others know. The
false-belief task (Wimmer & Perner, 1983) is the most common
test for this ability in children, and a modified version demon-
strates that even adults have difficulty completely disregarding
private knowledge when reasoning about false beliefs (Birch &
Bloom, 2007).
The modified task for adults was originally designed to inves-
tigate a specific curse-of-knowledge bias (Nickerson, 1999) by
comparing conditions of knowledge with conditions of naivety
(Birch & Bloom, 2007). We modified it further to detect more
general variation in theory-of-mind use. Adults read one of two
versions of a short scene and then predicted a protagonist’s be-
havior. In our task, the protagonist had the same knowledge in both
versions but participants received different privileged knowledge.
Diminished theory-of-mind use would be reflected by an increased
reliance on one’s own private knowledge. We predicted that happy
participants would be less likely to employ theory of mind, and
therefore be more influenced by their own private knowledge, than
would sad participants.
Method
Participants
One hundred University of Chicago students participated in
exchange for $4.
Procedure
This 2 ⫻ 2 between-subjects experiment included a mood
induction and a false-belief task, presented as two unrelated
studies.
Mood induction. As part of an “audio equipment evaluation,”
participants first evaluated the quality of a pair of headphones.
Participants in the happy condition picked one song from a list of
five “happy” songs. Participants in the sad condition picked one
song from a list of five “sad” songs. Song lists were preselected to
invoke the desired mood, based on informal pretesting. Partici-
pants then answered two headphone-evaluation questions, and an
abbreviated Positive and Negative Affect Schedule (PANAS) scale
as a manipulation check (calm, happy, angry, sad, excited, and
anxious; Watson, Clark, & Tellegen, 1988).
False-belief task. Participants then moved to another cubicle for
an ostensibly unrelated “second study” and received materials show-
ing two panels of a scene (see Figure 1). All participants saw Panel 1
and read, “This is Vicki. She finishes playing her violin and puts it in
the blue container. Then she goes outside to play.” Participants then
saw one of two randomly assigned versions of Panel 2, which ma-
nipulated their knowledge of the box that contained the violin. Par-
ticipants in the blue-box condition read: “While Vicki is outside
playing, her sister, Denise, comes into the room.” Participants in the
red-box condition read: “While Vicki is outside playing, her sister,
Denise, moves the violin to the red container.” All participants then
read: “Then, Denise rearranges the containers in the room until the
room looks like the picture below.” The picture depicts Denise in the
room, with the boxes rearranged. Critically, the red box in Panel 2 sits
where the blue box was in Panel 1, making it plausible that Vicki
might look in the red box.
All participants read, “When Vicki returns, she wants to play her
violin. What are the chances Vicki will first look for her violin in
each of the above containers?” Participants wrote their percentage
likelihood estimates in the spaces beneath each box.
The critical dependent variable was participants’ estimated like-
lihood that Vicki will look in the red box. Absolute predictions
about Vicki’s behavior can be influenced by countless factors (e.g.,
Will she notice the boxes have been moved?), but the important
measure for our hypothesis is the difference in estimates between
the two private-knowledge conditions. If likelihood-of-looking
estimates are higher for those who know it is in the red box than
for those who know it is in the blue box, this would reflect
egocentrism. To the extent that theory of mind is used to consider
only what Vicki believes, the influence of private knowledge will
be decreased. We predict less deliberate reasoning when partici-
pants are happy than when sad, and therefore greater private-
knowledge use when happy than when sad.
Results and Discussion
Three participants whose false-belief-task responses were more
than 3 SDs from the overall mean were removed from all analyses.
Mood Manipulation Checks
Participants reported being happier in the happy condition (M ⫽
3.65, SD ⫽ 0.72) than in the sad condition (M ⫽ 2.29, SD ⫽ 0.90),
t(95) ⫽ 8.23, p ⬍ .001, and reported being sadder in the sad
condition (M ⫽ 2.54, SD ⫽ 0.99) than in the happy condition
(M ⫽ 1.37, SD ⫽ 0.67), t(95) ⫽ 6.87, p ⬍ .001. Participants also
reported being significantly more excited in the happy condition
(M ⫽ 2.49, SD ⫽ 1.04) than in the sad condition (M ⫽ 1.48, SD ⫽
0.65), t(95) ⫽ 5.71, p ⬍ .001. There were no other between-
condition mood differences, ts ⬍ 1.
False-Belief Task
We predicted that participants in the happy condition would be
more influenced by their privileged location knowledge when
estimating the likelihood that Vicki would look in the red box than
would participants in the sad condition. A 2 (mood: happy vs.
sad) ⫻ 2 (location knowledge: red box vs. blue box) between-
subjects analysis of variance (ANOVA) yielded a significant main
effect of location knowledge, F(1, 93) ⫽ 5.53, p ⫽ .02, qualified
by the predicted interaction, F(1, 93) ⫽ 4.25, p ⬍ .05. Participants
in the happy condition predicted that Vicki was more likely to look
in the red box when they knew the violin was in the red box (M ⫽
21.01, SD ⫽ 18.49) than when they knew it was in the blue box
(M ⫽ 7.71, SD ⫽ 8.88), t(47) ⫽ 3.19, p ⬍ .01. Estimates in the sad
condition, however, did not differ between participants who knew
the violin was in the red box (M ⫽ 16.46, SD ⫽ 17.30) and those
726
BRIEF REPORTS

who knew it was in the blue box (M ⫽ 15.58, SD ⫽ 12.48),
t(46) ⬍ 1, ns. These data suggest that participants were less likely
to employ their theory of mind in the happy condition than in the
sad condition.
We designed Experiment 2 to expand on these findings by exam-
ining a different context (communication), using a different mood
induction (films), and utilizing more unobtrusive and online theory-
of-mind measures (behavioral observation and eye-movement).
Experiment 2
Language is inherently ambiguous. To communicate effectively,
a listener may need to consider a speaker’s knowledge or beliefs.
A date’s comment about one’s “fancy outfit,” for instance, could
be either sincere or sarcastic. Interpreting communication accu-
rately often requires employing one’s theory of mind to consider
the speaker’s beliefs, knowledge, or intentions.
We investigated how mood may influence the interpretation of
communication by inducing happy or sad moods in participants
playing a communication game. The participant and a confederate
“director” sat on opposite sides of an array of objects. The partic-
ipant followed the director’s instructions to move some of these
objects. Eleven of the 16 slots in the array were mutually visible,
whereas the other 5 were visible to the participant but occluded
from the director. This created a critical difference in perspective.
[Panel 1] This is Vicki. She finishes playing her violin and puts it in the blue container.
Then she goes outside to play.
blue
purple
red
green
[Panel 2] While Vicki is outside playing, her sister, Denise, …
[blue box condition] … comes into the room.
[red box condition] … moves the violin to the red container.
Then, Denise rearranges the containers in the room until the room
looks like the picture below.
____ %
____ %
____ %
____ %
When Vicki returns, she wants to play her violin. What are the chances Vicki will first look
for her violin in each of the above containers? Write your answers in the percentages in the
spaces provided under each container.
Note: All participants saw Panel 1. Participants saw either the blue-box version or the
red-box version of Panel 2. Color labels did not appear in the actual stimuli.
green
red
blue
purple
Figure 1. Modified false-belief task used in Experiment 1.
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BRIEF REPORTS

Egocentrism would be evident if participants thought that the
director was talking about objects that were visible only to them
(Keysar & Barr, 2002). For instance, the director might ask a
participant to “move the candle.” On critical trials, a competitor
object (e.g., a second candle) was included in the grid but occluded
from the director. Relying on an egocentric default in this case
would lead to confusion because there are two possible referents.
To overcome egocentrism and find the director’s intended object,
participants must use their theory of mind and rely only on what
the director can see.
We evaluated egocentric interference in two ways, as well as the
ability to recover from egocentric interference. First, we counted
behavioral manifestations of egocentrism, such as reaching for the
occluded object or asking for clarification. Second, we measured
the time taken to identify the target object when a competitor was
present versus absent. A longer delay, or more interference, indi-
cates diminished theory-of-mind use. We indexed the ability to
recover from initial egocentric processing by considering all trials
in which participants fixated on competitors. When people look at
an object, they may be considering it as a potential referent
(Keysar, Barr, Balin, & Brauner, 2000; Spivey & Tanenhaus,
1998). When participants fixated on competitors but did not reach
for them or ask for clarification, we considered it a case of
recovery.
We expected that participants induced to feel happy would again
be less likely to employ theory of mind and would therefore be
more prone to egocentric interference. Experiment 2 also included
a no-mood-induction control condition as an exploratory test of
whether the results are produced primarily by the induction of
happiness, of sadness, or both.
Method
Participants
Fifty-three University of Chicago students participated in ex-
change for $12. Data from 5 participants were discarded due to
miscalibrated equipment (3) or early termination due to discomfort
from the eye-tracker (2).
Apparatus
An SMI eye-tracker (SensoMotoric Instruments; Boston, MA)
recorded participants’ eye movements. Participants wore a helmet
with a small camera lens and a magnetic head-tracker that allowed
for natural movement. A computer integrated eye and head posi-
tion information to determine the gaze position and eye-fixation
coordinates.
Procedure
Training. The director received a picture of the grid that
illustrated, from her perspective, the desired final location of
objects. The pair’s goal was to collaborate in moving objects
around the grid to match the picture. Only the director could see
the picture, but only the participant could touch the objects. The
director therefore instructed the participant. A trained female con-
federate played the director, whom participants believed was a
naı¨ve participant. To ensure that participants understood the visual
occlusions, the experimenter reiterated the director’s ignorance of
objects in the occluded slots, and participants experienced the
director’s partially obstructed view by switching roles for one
practice round.
Mood induction. Participants next watched one randomly as-
signed movie clip known to induce happiness (When Harry Met
Sally; Reiner, 1989), sadness (The Champ; Zeffirelli, 1979), or
neither (Chicago Loop; WTTW, 1996). We borrowed the first two
from Gross and Levenson (1995), and validated all three in a
separate pretest. To refresh mood states during the communication
game, participants paused halfway through and spent 3 min think-
ing of events that corresponded with the mood in the movie.
Participants in the neutral condition recalled the last items they
purchased from the grocery store.
Communication game. Participants next played eight rounds
of the communication game. For each round, there was a target
object in one of the 11 mutually visible slots. Before receiving
instructions, participants fixated on the center of the grid. Partic-
ipants were free to move their eyes as soon as the director began
the instructions. The director’s instructions for half of the trials
were potentially confusing because a competitor object was
present in one of the occluded slots (“competitor present”). There
was no competitor present in the other trials (“competitor absent”).
Target objects were presented in random order, except that no
more than two target objects from the same condition appeared
consecutively.
Measures. The behavioral index of egocentric interference
was the number of trials in which each participant (a) reached for
or moved the competitor or (b) asked the director for clarification.
The latency to identify the target object was indexed by the
participant’s final fixation on it before reaching. Eye fixations
were coded within a temporal window that began at the noun
phrase (e.g., the “c” in “candle”), and ended when the participant
finally identified the target. In the few cases when participants
did not fixate on the target, the hand touch was considered the
end of the window. We counted a fixation on an object if the
eye gaze remained in its slot for at least 100 ms consecutively.
The delay caused by the presence of the competitor objects,
measured by the time increase in competitor-present trials rel-
ative to competitor-absent trials, constituted our second mea-
sure of egocentric interference. The measure of recovery was
the conditional probability, given fixation on the competitor, of
resolving the interference without asking for clarification or
reaching for the competitor.
Results and Discussion
Egocentric Interference
Egocentric behavior. Without the competitor, participants
showed no egocentric behavior. The presence of the competitor,
however, resulted in significantly different levels of egocentric
behavior in the three mood conditions, F(2, 45) ⫽ 4.98, p ⫽ .01.
A planned comparison demonstrates that those in the happy con-
dition behaved more egocentrically (M ⫽ 1.8, SD ⫽ 1.2), across
the four competitor-present trials than did those in the sad condi-
tion (M ⫽ 0.7, SD ⫽ 0.8), t(30) ⫽ 2.89, p ⬍ .01. Participants in
the happy condition also behaved more egocentrically than those
in the neutral condition (M ⫽ 0.8, SD ⫽ 1.1), t(30) ⫽ 2.39, p ⫽
.02. The sad and neutral conditions did not differ, t(30) ⬍ 1, ns.
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BRIEF REPORTS

Delay. To avoid inflating the effects with long latencies, we
truncated them at 3 SDs from the mean. The presence of the com-
petitor slowed final fixation on the target object more in the happy
condition than in the sad condition (see Figure 2). We submitted
the final-fixation times to a 3 (mood: happy, sad, neutral) ⫻ 2
(competitor: present vs. absent) mixed-model ANOVA, with com-
petitor as a within-participants factor. This yielded a main effect
for competitor, F(1, 45) ⫽ 34.24, p ⬍ .01, qualified by the
predicted interaction, F(1, 45) ⫽ 4.69, p ⬍ .05. A planned 2
(mood: happy vs. sad) ⫻ 2 (competitor: present vs. absent) mixed-
model ANOVA demonstrates that the delay in final fixations
caused by the competitor was significantly larger in the happy than
the sad condition, F(1, 30) ⫽ 5.68, p ⬍ .05. Exploratory 2 ⫻ 2
ANOVAs demonstrated that the delay in the happy condition was
also significantly greater than the delay in the neutral condition,
F(1, 30) ⫽ 7.03, p ⬍ .05, but the sad and neutral conditions did not
differ, F ⬍ 1.
Recovery
The proportion of competitor-present trials that included fixa-
tion on a competitor was nearly identical across the three mood
conditions (67%, 66%, 61%, for happy, sad, and neutral, respec-
tively). Among those trials, recovery rates were lower in the happy
condition (44%) than in the sad (76%), ␹
2
(1, N ⫽ 85) ⫽ 9.07, p ⬍
.01, or neutral conditions (74%), ␹
2
(1, N ⫽ 82) ⫽ 7.67, p ⬍ .01.
The three measures thus converge to show that participants in a
happy mood are more prone to egocentric interference and less
likely to recover from it than those in a sad mood. We also found
that theory-of-mind use was disrupted by happiness more than it
was facilitated by sadness compared to a neutral condition. We
doubt this second finding is a systematic feature of judgment, but
suspect that it is a product of this particular paradigm in which
there may be relatively little room for improvement in perfor-
mance relative to the baseline condition but considerable room for
decrements in performance. Further research would be necessary
to address this conclusively.
General Discussion
People make inferences about others’ mental states in a wide
variety of moods. Our experiments suggest that these mood states
have important consequences for mental-state inferences, such that
those in a happy mood may be less likely to utilize their theory of
mind than those in a sad mood. These results are important not
only for the practical insights they provide into what affects
everyday theory-of-mind use, but also for the theoretical insights
into how people make mental state inferences in the first place. In
particular, these results suggest that theory of mind requires de-
liberative processing to inhibit an egocentric assessment that is
often more readily accessible than is specific knowledge about
others. Happy people tend to rely on this egocentric default,
whereas sad people incorporate knowledge about others more
deliberately. These differential effects of mood are inconsistent
with a purely automatic account of theory-of-mind use.
It is important to clarify that these results do not demonstrate
that happiness will always increase egocentric bias, nor that ego-
centric bias will necessarily decrease accuracy. First, accuracy
depends on the structure of the situation. Research often relies on
tasks where one’s own perspective differs from another’s perspec-
tive. An egocentric process under these circumstances leads to
mistaken inferences, but when perspectives overlap, egocentric
reasoning should produce more accurate judgments (Hoch, 1987).
Second, mental-state inferences need not always begin with an
egocentric default, but may instead evoke rapidly accessible ste-
reotypes when others appear to be very different from the self
(Ames, 2004; Clement & Krueger, 2002). Happiness, compared
with a neutral state (and presumably sadness as well), tends to
increase stereotype use in judgment (e.g., Bodenhausen, Kramer,
&Su¨sser, 1994). The general principle governing these findings is
that happiness increases reliance on readily accessible defaults in
judgment, whereas sadness diminishes reliance on such defaults
(for a review, see Clore & Huntsinger, 2007). In mental-state
inferences, happiness increases reliance on these defaults— be
they stereotypes or egocentric knowledge—whereas sadness pro-
motes the elaboration of individuating information about others’
mental states through deliberate theory-of-mind use.
More practically speaking, these results provide insight into an
important source of systematic variability in theory-of-mind use.
In both of our experiments, people utilized their knowledge about
others’ knowledge when they were feeling sad and this made their
inferences less biased. To the extent that individuals’ mental states
are discrepant, then, happy mind readers may find themselves
sadly mistaken.
References
Ames, D. R. (2004). Inside the mind reader’s tool kit: Projection and
stereotyping in mental state inference. Journal of Personality and Social
Psychology, 87, 340 –353.
Apperly, I. A., Riggs, K. J., Simpson, A., Samson, D., & Chiavarino, C.
(2006). Is belief reasoning automatic? Psychological Science, 17,
841– 844.
Apperly, I. A., Samson, D., & Humphreys, G. W. (2005). Domain speci-
ficity and theory of mind: Evaluating neuropsychological evidence.
Trends in Cognitive Sciences, 9, 572–577.
Birch, S., & Bloom, P. (2007). The curse of knowledge in reasoning about
false beliefs. Psychological Science, 18, 382–386.
0
1000
2000
3000
4000
5000
6000
Happy Neutral Sad
Emotion Condition
Latency to Final Fixation on Target (ms)
Competitor Absent
Competitor Present
Figure 2. Latency to final fixation on target object (ms) as a function of
mood (Experiment 2). Bars represent standard errors.
729
BRIEF REPORTS

Bless, H., Igou, E. R. (2005). Mood and the use of general knowledge
structures in judgment and decision making. In T. Betsch & S. Haber-
stroh (Eds.), The routines of decision making (pp. 193–210). San Diego,
CA: Academic.
Bodenhausen, G. V., Kramer, G. P., & Su¨sser, K. (1994). Happiness and
stereotypic thinking in social judgment. Journal of Personality and
Social Psychology, 66, 621–632.
Bodenhausen, G. V., Mussweiler, T., Gabriel, S., & Moreno, K. N. (2001).
Affective influences on stereotyping and intergroup relations. In J. P.
Forgas (Ed.), Handbook of affect and social cognition (pp. 319 –343).
Mahwah, NJ: Erlbaum.
Chaiken, S., & Trope, Y. (Eds.) (1999). Dual-process theories in social
psychology. New York: Guilford.
Clement, R. W., & Krueger, J. (2002). Social categorization moderates
social projection. Journal of Experimental Social Psychology, 38,
219 –231.
Clore, G. L., & Huntsinger, J. R. (2007). How moods inform judgment and
regulate thought. Trends in Cognitive Science, 11, 393–399.
Epley, N., Keysar, B., Van Boven, L., & Gilovich, T. (2004). Perspective-
taking as egocentric anchoring and adjustment. Journal of Personality
and Social Psychology, 87, 327–339.
Epley, N., Morewedge, C. K., & Keysar, B. (2004). Perspective taking in
children and adults: Equivalent egocentrism but differential correction.
Journal of Experimental Social Psychology, 40, 760 –768.
Fodor, J. A. (1985). Precis of the modularity of mind. The Behavioral and
Brain Sciences, 8, 1–42.
Forgas, J. P. (1995). Mood and judgment: The affect infusion model
(AIM). Psychological Bulletin, 117, 39– 66.
Friedman, O., & Leslie, A. M. (2004). Mechanisms of belief-desire rea-
soning: Inhibition and bias. Psychological Science, 15, 547–552.
Gross, J. J., & Levenson, R. W. (1995). Mood elicitation using films.
Cognition and Mood, 9, 87–108.
Hoch, S. J. (1987). : Perceived consensus and predictive accuracy: The
pros and cons of projection. Journal of Personality and Social Psychol-
ogy, 53, 221–234.
Kahneman, D. (2003). A perspective on judgment and choice: Mapping
bounded rationality. American Psychologist, 58, 697–720.
Keysar, B., & Barr, D. J. (2002). Self-anchoring in conversation: Why
language users do not do what they “should”. In T. Gilovich, D. Griffin,
& D. Kahneman (Eds.). Heuristics and biases: The psychology of
intuitive judgment (pp. 150 –166). New York: Cambridge University
Press.
Keysar, B., Barr, D. J., Balin, J. A., & Brauner, J. S. (2000). Taking
perspective in conversation: The role of mutual knowledge in compre-
hension. Psychological Science, 11, 32–38.
Lin, S., Keysar, B., & Epley, N. (2008). The role of effortful attention
in interpreting the behavior of others. Unpublished manuscript, Uni-
versity of Chicago.
Nickerson, R. S. (1999). How we know—And sometimes misjudge—What
others know: Imputing one’s own knowledge to others. Psychological
Bulletin, 125, 737–759.
Oaksford, M., Morris, F., Grainger, B., & Williams, J. M. G. (1996). Mood,
reasoning, and central executive processes. Journal of Experimental
Psychology: Learning, Memory, and Cognition, 22, 476 –492.
Phillips, L. H., Bull, R., Adams, E., & Fraser, L. (2002). Positive mood and
executive function: Evidence from Stroop and fluency tasks. Emotion, 2,
12–22.
Reiner, R. (Director). (1989). When Harry met Sally [Motion picture].
United States: Castle Rock Entertainment.
Sloman, S. A. (1996). The empirical case for two systems of reasoning.
Psychological Bulletin, 119, 3–22.
Sperber, D., & Wilson, D. (2002). Pragmatics, modularity and mind-
reading. Mind & Language, 17, 3–23.
Spivey, M. J., & Tannenhaus, M. K. (1998). Syntactic ambiguity resolution
in discourse: Modeling the effects of referential context and lexical
frequency. Journal of Experimental Psychology: Learning, Memory, and
Cognition, 24, 1521–1543.
Stone, V. E., Baron-Cohen, S., & Knight, R. T. (1998). Frontal lobe
contributions to theory of mind. Journal of Cognitive Neuroscience, 10,
640 – 656.
Watson, D., Clark, L. A., Tellegen, A. (1988). Development and validation
of brief measures of positive and negative affect: The PANAS scales.
Journal of Personality and Social Psychology, 54, 1063–1070.
Wimmer, H., & Perner, J. (1983). Beliefs about beliefs: Representation and
constraining function of wrong beliefs in young children’s understand-
ing of deception. Cognition, 13, 103–128.
WTTW, Channel 11 (Producer). (1996). Chicago’s loop: A walking tour
[Motion Picture]. (Available from WTTW11, The Chicago Production
Center, 5400 N St. Louis Avenue, Chicago, IL 60625)
Zeffrelli, F. (Director). (1979). The champ [Motion Picture]. United States:
MGM.
Received November 16, 2007
Revision received June 12, 2008
Accepted June 24, 2008 䡲
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