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Essay questions for: Kraft, T.L. & Pressman, S.D. (2012). Grin and Bear It: The Influence of Manipulated Facial Expression on the Stress Response.Psychological Science, 23(11)1372–1378.
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Research Article
Grin and Bear It: The Influence of
Manipulated Facial Expression on the
Stress Response
Psychological Science
23(11) 1372–1378
© The Author(s) 2012
Reprints and permission:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/0956797612445312
http://pss.sagepub.com
Tara L. Kraft and Sarah D. Pressman
University of Kansas
Abstract
In the study reported here, we investigated whether covertly manipulating positive facial expressions would influence
cardiovascular and affective responses to stress. Participants (N = 170) naive to the purpose of the study completed two
different stressful tasks while holding chopsticks in their mouths in a manner that produced a Duchenne smile, a standard
smile, or a neutral expression. Awareness was manipulated by explicitly asking half of all participants in the smiling groups to
smile (and giving the other half no instructions related to smiling). Findings revealed that all smiling participants, regardless
of whether they were aware of smiling, had lower heart rates during stress recovery than the neutral group did, with a slight
advantage for those with Duchenne smiles. Participants in the smiling groups who were not explicitly asked to smile reported
less of a decrease in positive affect during a stressful task than did the neutral group. These findings show that there are both
physiological and psychological benefits from maintaining positive facial expressions during stress.
Keywords
emotions, facial expressions, well-being, health, stress reactions
Received 9/19/11; Revision accepted 3/2/12
In the past decade, scientists have produced a wealth of research
connecting positive affect to physical and psychological wellbeing (see Lyubomirsky, King, & Diener, 2005; Pressman &
Cohen, 2005). Although most studies have focused on selfreported positive affect, observational methods have also shed
light on these associations. For example, facial expressions
indicating smiles of “nonenjoyment” have been shown to
differentiate subjects with and without myocardial ischemia
(Rosenberg et al., 2001). Similarly, smiling in photographs has
been associated with well-being outcomes decades later (Abel
& Kruger, 2010; Harker & Keltner, 2001), which raises the
possibility that facial expression is a health-relevant emotion
indicator.
Following the tradition of James (1890), many researchers
have proposed that emotions are the consequence of facial expressions (and other behaviors) rather than the more commonly
considered reverse direction. For example, self-perception theory states that acting as though one feels a certain way will lead
to that feeling (Bem, 1972; Laird, 1974). Especially relevant to
facial-expression research is the related facial-feedback hypothesis, which states that activating facial muscles leads to the psychological experience of emotion (Tourangeau & Ellsworth,
1979). In a classic study demonstrating the facial-feedback
hypothesis, Strack, Martin, and Stepper (1988) had participants
place pencils in their mouths in ways that activated facial muscles involved in smiling (or not smiling) while rating cartoons
for funniness. Participants whose mouths were manipulated to
smile rated cartoons as funnier than did participants in other
conditions, despite a cover story linking the mouth-pencil to
research on physical impairment.
Facial-expression researchers have long agreed that not all
smiles are equal. Ekman (2001) suggested that as many as 50
kinds of smiles exist; however, most research focuses on the
distinction between “genuine” and “standard” smiles based
on activation of the orbicularis oculi muscle surrounding the
eye. A “standard” smile engages the zygomaticus major muscles around the mouth, but only a “genuine” Duchenne smile
engages both zygomaticus major and orbicularis oculi muscles
(Duchenne, 1862/1990; Ekman & Friesen, 1982). Ekman,
Davidson, and Friesen (1990) found that Duchenne smiling
Corresponding Authors:
Tara L. Kraft, Department of Psychology, University of Kansas, 1415
Jayhawk Blvd., Lawrence, KS 66045
E-mail: kraft.tara@gmail.com
Sarah D. Pressman, Department of Psychology, University of Kansas, 1415
Jayhawk Blvd., Lawrence, KS 66045
E-mail: pressman@ku.edu
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Grin and Bear It
was seen more frequently when viewing pleasant films than
when viewing unpleasant films and has been associated with
activity in the left frontal and anterior temporal lobes, areas
previously associated with positive affect (e.g., Davidson,
1992). Furthermore, Ekman and Davidson (1993) found that
voluntarily producing a Duchenne smile activated the same
brain regions responsible for positive affect as did involuntary
Duchenne smiles stimulated by outside sources. This supports
the facial-feedback hypothesis, given that the consequences
associated with voluntary and involuntary activation of facial
muscles were remarkably similar in the brain.
One important outcome that might be related to positive
facial expressions is the cardiovascular stress response, a measure tied to future heart-health outcomes (e.g., Treiber et al.,
2001). Although experimental facial manipulation has not
been tied to this outcome directly, naturally occurring and
manipulated positive affect has been linked to “healthier”
cardiovascular stress recovery (i.e., quicker return toward resting heart function; Fredrickson & Levenson, 1998; Steptoe,
Gibson, Hamer, & Wardle, 2007). It is notable that Fredrickson and Levenson (1998) also found that participants who
spontaneously smiled during stress returned to resting levels
of cardiovascular function more rapidly than did nonsmiling
counterparts. This suggests that smiling may be particularly
helpful in speeding stress recovery by reducing negative aftereffects of stress. This is consistent with Fredrickson, Mancuso,
Branigan, and Tugade’s (2000) “undoing hypothesis” of positive affect, which specifically postulates better recovery as a
pathway connecting positive affect to well-being benefits. It is
also in line with the more general stress-buffering model of
positive affect and health (Pressman & Cohen, 2005), which
asserts that positive feelings may guard against the negative
physiological consequences of stress at a variety of times,
including before, during, or after stress. Because smiling was
not randomly assigned in the Fredrickson and Levenson
(1998) study, it remains unclear whether this finding was due
to facial expression directly or was simply the result of differences in emotional states or traits.
In the current study, we sought to better understand whether
the facial changes that occur in smiling might be partially
responsible for observed benefits connecting positive affect to
improved stress recovery and whether smile types would have
differential effects. Specifically, would “sincere” Duchenne
smiling produce greater stress-recovery benefits than would
standard smiling (or no smile)? Awareness of smiling was also
manipulated to determine whether benefits were present when
cognitive awareness of facial expression was absent. Past
studies of the facial-feedback hypothesis and related selfperception work have purposely avoided awareness to prove
the expression-feeling connection without cognition. In the
case of stress, however, facial-muscle activation may not
have the same power given the conflicting emotion and autonomic arousal signals (i.e., from pain and threat). Furthermore,
studies have shown that purposely “faking” positive facialemotion expression in customer service leads to increased
burnout and employee error (e.g., Goldberg & Grandey, 2007),
which suggests that awareness of artificial smiling may be
harmful. Finally, emotion changes that occurred with condition assignment were assessed. On the basis of the facial-feedback hypothesis, we expected smilers to report greater positive
affect than nonsmilers; however, in the stress context, it was
anticipated that this would instead manifest as a lesser decrease
in positive affect and a smaller increase in negative affect.
Method
Participants and procedure
One hundred seventy healthy participants (age = 18–25 years;
66% female, 34% male; 79% Caucasian, 21% other) were
recruited from a large Midwestern university and screened for
facial muscular disorder, lack of English fluency, and psychological disorder. Participants were randomly assigned to a
neutral-expression control group (n = 58), a standard-smile
group (n = 56), or a Duchenne-smile group (n = 56). Groups
were asked to hold chopsticks in their mouths with their teeth
by mimicking the holding pattern of a research assistant
(who was blind to the study hypotheses) and a photo example
(Fig. 1).
Participants in the Duchenne-smile group were trained to
activate zygomaticus major and orbicularis oculi muscles, participants in the standard-smile group were trained to activate
zygomaticus major muscles, and participants in the neutral
group were simply instructed to hold the chopsticks gently in
their mouths with their faces relaxed. Participants were given
positioning assistance, image examples, experimenter instruction, and verbal correction during the study. To ensure that correct muscles were activated, two research assistants trained
with the Facial Action Coding System (Ekman & Friesen,
1978) coded videos of participants. On a scale from 1 (poor
adherence) to 5 (excellent adherence), the neutral group had
the highest average adherence (3.35), with the standard-smile
group averaging 1.90 and the Duchenne-smile group averaging 2.60.
Participants were given a cover story stating that this was a
“multitasking study” (similar in nature to the cover story used
by Strack et al., 1988) to prevent awareness or reactance to
smiling. Because we were also interested in participants’
awareness of smiling, half the participants in each smiling
group (n = 28 per group) were additionally told to smile during
the instruction period (the other half were given no additional
instructions regarding their facial expressions).
After completing baseline questionnaires, participants’
heart rate was monitored in beats per minute (bpm) using an
automated cuff (Dinamap ProCare Auscultatory 400 Vital
Signs Monitor, Lafayette Instrument Company, Lafayette, IN)
that inflated approximately every 90 s over the course of the
study. Heart rate was used as the primary outcome, as it is one
of the most frequently measured variables in cardiovascular
stress studies (e.g., Turner, 1994, p. 45). It is a reliable measure
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Kraft, Pressman
Fig. 1. Examples of photographs shown to participants in the neutral group (left), standard-smile group (middle), and Duchenne-smile group (right)
to help them form the appropriate expressions.
that is easily assessed, and it increases in response to a large
range of stressors. Following a 10-min resting period, participants completed a 2-min star-tracing task. This stress-inducing
task requires participants to place their nondominant hand
inside a box and repeatedly trace a star while viewing only a
mirror image of the star and their hand. If they strayed from
the outline of the star, they received negative auditory feedback. Participants were strongly encouraged to be accurate
and were also given incorrect information about performance
standards to increase stress (i.e., they were told that the task
average was eight tracings with fewer than 25 errors). They
were promised an incentive (chocolate) if they could match
this unattainable goal. Average participants could complete
two tracings in 2 min with over 25 errors. This task was followed by a 5-min recovery period.
Next, participants completed a cold-pressor stress task in
which their hand was submerged in ice water (2–3 °C) for 1
min. Participants then recovered again for 5 min. Tasks were
not counterbalanced because of lasting pain from the cold.
Chopsticks were held in the mouth only during the stress
period (not during the recovery period), and verbal reminders
were given when facial expressions lapsed. State affect, stress,
task difficulty, and facial-muscle fatigue were measured at
baseline and following each task. Participants were probed
during debriefing for knowledge of study hypotheses. Only
one individual identified that the study’s purpose was to examine smiling.
Positive- and negative-affect change scores were calculated
from baseline for each task using 16 items drawn from the
factor-analyzed version of the Profile of Mood States (McNair,
Lorr, & Droppleman, 1971; Usala & Hertzog, 1989). Baseline
stress was measured using the Perceived Stress Scale (Cohen,
Kamarck, & Mermelstein, 1983) and via momentary assessments throughout the study, in which participants rated how
stressful they found each task on a 10-point scale. Behavioral
variables known to correlate with cardiovascular functioning
were measured at baseline, including body mass index, sleep,
smoking, alcohol consumption, exercise, and drug use.
Statistical approach
For cardiovascular-recovery analyses, we used repeated measures analyses of covariance, with five time intervals, including the peak stress point of each task and four subsequent 90-s
intervals following each task. This analysis accounted for differences from the final reactivity point to the end of the recovery period with between-subjects effects being conceptually
similar to change scores from reactivity to recovery. To analyze state affect changes during tasks, we used univariate analyses of covariance. The main analyses of interest were
comparisons between (a) the neutral versus the smiling groups,
(b) the Duchenne-smile versus the standard-smile groups, and
(c) the aware versus the nonaware groups. In all analyses,
covariates significantly associated with the outcome of interest were controlled for. Variables included (when significant)
were age, race, sex, body mass index, baseline stress, sleep,
smoking, alcohol use, exercise, condition adherence, perceived task difficulty, self-reported facial-muscle fatigue, perceived task stress, and stress reactivity. Group differences in
stress reactivity were not found for any contrasts of interest.
Results
An overall uncorrected analysis of variance of all five groups
revealed significant differences during recovery following the
star-tracer task, with aware standard smilers showing the lowest
recovery heart rate levels (M = 65.75 bpm), followed by nonaware Duchenne smilers (M = 66.50 bpm), aware Duchenne
smilers (M = 67.40 bpm), the neutral group (M = 71.36 bpm),
and nonaware standard smilers (M = 72.73 bpm), F(4, 139) =
4.68, p < .01. Uncorrected analyses found marginally significant
differences between groups following the cold-pressor task,
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Grin and Bear It
a
Neutral Condition
Standard-Smile Condition
Duchenne-Smile Condition
84
Heart Rate
80
76
72
68
64
60
0
90
180
270
360
270
360
Time (s)
b
Neutral Condition
Nonaware Condition
Aware Condition
84
80
Heart Rate
with aware standard smilers (M = 66.33 bpm) showing the lowest heart rate, followed by aware Duchenne smilers (M = 66.34
bpm), nonaware Duchenne smilers (M = 66.86 bpm), the neutral group (M = 70.91 bpm), and nonaware standard smilers
(M = 71.43 bpm), F(4, 142) = 2.27, p = .06. After accounting for
significant covariates, we found clear and consistent group differences overall and between individual contrasts, with smiling
groups showing lower levels of heart rate during recovery than
the neutral group. Average corrected means during recovery for
individual contrasts are reported when main (between-subjects)
effects are significant.
During recovery from the star-tracer task, the following
groups had significantly lower heart rates than the neutral
group: the two smile groups combined (Msmile = 68.19 bpm vs.
Mneutral = 71.45 bpm), F(1, 117) = 3.95, p = .05, Duchenne
smilers only (MDuchenne = 66.40 bpm vs. Mneutral = 71.69 bpm),
F(1, 74) = 6.71, p < .05, and aware smilers (Maware = 66.60
bpm vs. Mneutral = 71.29 bpm), F(1, 72) = 5.40, p < .05. When
comparing three groups, significant heart rate recovery differences were found between the neutral group, standard smilers,
and Duchenne smilers, as well as between the neutral group,
aware smilers, and nonaware smilers (p < .05; Fig. 2).
Results for recovery following the cold-pressor task were
similar. The following groups had lower heart rates than the
neutral group: the two smile groups combined (Msmile = 67.37
bpm vs. Mneutral = 71.69 bpm), F(1, 109) = 4.34, p < .05, Duchenne smilers only (MDuchenne = 65.37 bpm vs. Mneutral = 72.02
bpm), F(1, 69) = 9.12, p < .05, aware smilers (Maware = 66.66
bpm vs. Mneutral = 71.48 bpm), F(1, 66) = 4.61, p < .05, and nonaware smilers, who showed only marginally lower heart rates
than the neutral group (Mnonaware = 68.34 bpm vs. Mneutral = 72.52
bpm), F(1, 68) = 2.78, p = .10. Duchenne smilers also had marginally lower heart rates than did standard smilers (MDuchenne =
64.98 bpm vs. Mstandard = 69.32 bpm), F(1, 76) = 3.61, p = .06.
When the three groups were compared in one model, significant
differences were again found between the neutral group, standard smilers, and Duchenne smilers, as well as between the neutral group, aware smilers, and nonaware smilers (Fig. 3).
Overall, uncorrected analyses of variance examining selfreported affect changes during tasks did not reveal significant
group differences. However, when corrected individual contrasts were examined, affect changes were in the expected direction, although small, often nonsignificant, and only following
the cold-pressor task. Specifically, following cold stress, nonaware smilers (M = –0.32) showed less of a decrease in positive
affect from baseline than the neutral group did (M = –0.65), F(1,
71) = 4.21, p < .05, all smilers showed marginally less of a
decrease in positive affect (Msmile = –0.36 vs. Mneutral = –0.58),
F(1, 115) = 2.56, p = .1, and Duchenne smilers had marginally
less of a decrease in positive affect (MDuchenne = –0.36 vs. Mneutral =
–0.60), F(1, 75) = 2.47, p = .1. Further, nonaware smilers
showed a marginal decrease in negative affect from baseline; in
contrast, the neutral group showed an increase (Mnonaware =
–0.17 vs. Mneutral = 0.07), F(1, 73) = 2.78, p = .1.
76
72
68
64
60
0
90
180
Time (s)
Fig. 2. Mean heart rate (in beats per minute) during the recovery period
following the star-tracer task as a function of measurement occasion and
condition. Results are shown separately for (a) the three facial-expression
groups and (b) the aware and nonaware subgroups of the two smiling
groups (collapsed across groups). The analysis controlled for sex, condition
adherence, baseline perceived stress, perceived task difficulty, task stress, and
facial-muscle fatigue. Error bars represent standard errors.
Discussion
This is the first study to show that experimentally assigned
positive facial manipulation—with or without awareness of
expression—has a direct impact on cardiovascular stress
recovery. This may be relevant for health given that cardiovascular recovery is an outcome known to predict future disease
(e.g., Steptoe & Marmot, 2005) and mortality (e.g., Cole,
Blackstone, Pashkow, Snader, & Lauer, 1999). Duchenne
smiling was particularly advantageous, which indicates that
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Kraft, Pressman
a
Neutral Condition
Standard-Smile Condition
Duchenne-Smile Condition
84
Heart Rate
80
76
72
68
64
60
0
90
180
270
360
270
360
Time (s)
b
Neutral Condition
Nonaware Condition
84
Aware Condition
Heart Rate
80
76
72
68
64
60
0
90
180
Time (s)
Fig. 3. Mean heart rate (in beats per minute) during the recovery period
following the cold-pressor task as a function of measurement occasion and
condition. Results are shown separately for (a) the three facial-expression
groups and (b) the aware and nonaware subgroups of the two smiling groups
(collapsed across groups). The analysis controlled for condition adherence,
exercise, baseline perceived stress, perceived task difficulty, and facial-muscle
fatigue. Error bars represent standard errors.
sincere smiles may be more effective for stress recovery than
standard smiles. To our knowledge, this is the first indication
that Duchenne smiling plays a role in the stress response. Note
that the chopsticks were in place only during stress; thus, our
results indicate that smiling was beneficial for a period of time
after the stressors and facial-muscle activation had ended.
These findings match the “stress undoing” predictions of
Fredrickson et al. (2000) given that effects for smiling were
found only after the stressors had occurred
Aware smiling did produce a small advantage in stress
recovery as compared with nonaware smiling. Although
results of the aware and nonaware groups were not different
from each other, the results from those who heard the word
“smile” during instruction were significantly different from
the results of the neutral condition; however, nonaware individuals had only marginal or nonsignificant recovery advantages. This may mean that even though individuals were
unaware that the study was examining smiling, awareness that
their face was positioned like a smile offered some advantage,
perhaps by priming the idea of positive affect prior to a stressful period. Nonetheless, nonaware smilers had similar but
lesser heart rate benefits without this knowledge.
Small and marginal facial influences on affect were found
for those smiling during cold stress, consistent with initial
hypotheses. This was true for both smiling groups compared
with the neutral group but only for those unaware of smiling.
Unlike in past facial-feedback hypothesis manipulations, smiling did not increase positive affect but instead reduced the detrimental affect influences of stress. These findings are consistent
with emotional blunting and affect-processing changes seen in
participants told to inhibit facial-emotion expression (e.g.
Duclos & Laird, 2001) and participants unable to manipulate
facial muscles because of botulinum-toxin-induced paralysis
(Davis, Senghas, Brandt, & Ochsner, 2010; Havas, Glenberg,
Gutowski, Lucarelli, & Davidson, 2010). It is likely that the prevention of negative expressions during stress in addition to
forced positive expression contributed to these results. It is
interesting to note that, given the lack of affect findings for the
star task, state emotion change may not be the mediator connecting facial expression to heart rate. Post hoc analyses testing
positive affect, negative affect, and their arousal subcomponents
as possible mediators of found effects revealed that reported
changes accounted for a nonsignificant amount of variance
(10% or less). If smiling is altering emotion in an important
way, it is occurring outside the range of self-report awareness. It
is also possible that emotion changes from artificial facial
manipulation during stress are not easily tested by self-report,
because of conflicting feelings. This also raises the intriguing
possibility that there are pathways connecting facial-muscle
activity to autonomic activity that do not require conscious
emotion.
The generalizability of these findings to the real world is
questionable given the artificiality of the setting and manipulation. Also, considering that long-lasting emotion-incongruent
displays have been shown to be harmful (e.g., Goldberg &
Grandey, 2007), it is important to consider other factors,
such as duration, context, and frequency. More likely is
the possibility that “fake” smiling may be useful for brief or
painful stressors, such as receiving an injection (see Lanzetta,
Cartwright-Smith, & Eleck, 1976, for a similar paradigm).
Consistent with these ideas, our results showed affect advantages only in nonaware smilers. This may indicate that
individuals who had some idea that their faces were in an
incongruent emotion position did not receive the affect benefits. This study also looked at heart rate as the only dependent
variable of interest. Blood pressure was assessed but not
reported because of space constraints and lack of consistency
in findings. Although blood pressure was sometimes consistent
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Grin and Bear It
with heart rate (e.g., Duchenne smilers showed better results
following the two stress tasks than either standard smilers or
the neutral group did), many of the contrasts were not significant, which indicates that smiling may have less of an impact on
vasculature changes. Future work should examine additional
cardiovascular indicators, use more precise beat-by-beat measures of blood pressure, and explore possible pathways for why
these outcomes have differential associations with smiling.
Overall, these results suggest that the adage “grin and bear
it” does have proven value and that the benefits of smiling
through stress should not be ignored. Given that facial expression is a ubiquitous part of everyday communication, future
studies examining stress responses in individuals with facial
paralysis or impairment are warranted, as are studies investigating the relative benefits of different smile types.
Acknowledgments
The two authors contributed equally to this project and are listed
alphabetically. We express our great gratitude to Dena Rhodes, Emily
Hooker, and Vanessa Rupp for their hard work on this study and our
thanks to the many other undergraduate research assistants who
assisted with this project. Finally, we would like to thank Pete
Gianaros for his comments on this manuscript.
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interest with
respect to their authorship or the publication of this article.
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