Facial Feedback Hypothesis (Definition + Examples)

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We show our emotions through our facial expressions. We smile when we are happy and frown when we are angry. This is one of the ways we communicate our feelings to others. But did you know it might also work the other way around? Our facial expressions can influence our emotions. 

This is the main assumption of the facial feedback hypothesis. 

What Is the Facial Feedback Hypothesis?

The facial feedback hypothesis suggests that contractions of the facial muscles communicate our feelings not only to others but also to ourselves. In other words, our facial movements directly influence our emotional state and our mood even if the circumstances around us don't change!

facial feedback hypothesis

All humans are thought to share seven basic emotions : happiness, surprise, contempt, disgust, sadness, anger, and fear. Each one of these emotions has unique facial expressions associated with it. Raised lip corners and crow’s feet wrinkles around eyes mean joy, while tightened lips and eyebrows pulled down signify contempt. 

But facial expressions are more than just representations of our emotions. They contribute to and sustain what we are feeling. 

Example of Facial Feedback Hypothesis at Work

The best example of this theory is easy to perform. Go to the mirror and smile. Keep smiling...keep smiling! Even if you were in a bad mood before, you are likely to lighten up and maybe even start laughing! (This is much more fun to try than scowling!)

Who First Wrote About Facial Feedback Hypothesis?

The origins of facial feedback hypothesis can be traced back to the 1870s when Charles Darwin conducted one of the first studies on how we recognize emotion in faces. Darwin suggested that facial expressions of emotions are innate and universal across cultures and societies. In his book The Expression of the Emotions in Man and Animals, he argued that all humans and animals show emotion through similar behaviors. 

Paul Ekman's Contributions to Facial Feedback Hypothesis

Numerous studies have since confirmed Darwin’s idea that facial expressions are not socially learned. Instead, they appear to be biological in nature. In the 1950s, American psychologist Paul Ekman did extensive research on facial expressions in different cultures. His findings were in line with Darwin’s idea of universality. Even the members of most remote and isolated tribes portrayed basic emotions using the same facial movements as we do.

What’s more, expressing emotions through facial movements is not any different in people who were born blind. Although they can neither see nor imitate others, they still use the same facial expressions to project their emotions as sighted people do. 

There are, however, a few exceptions. 

People with schizophrenia and individuals on the autism spectrum have not only difficulty recognizing nonverbal expressions of emotions, but also producing these spontaneous expressions themselves. They typically either remain expressionless or have looks that are hard to interpret.

The James-Lange theory of emotion

A decade after Darwin’s study, the father of American psychology William James and Danish physiologist Carl Lange proposed a new theory of emotion that has served as a basis for the facial feedback hypothesis. ​ The James-Lange Theory of Emotion implies that our facial expressions and other physiological changes create our emotions. 

physiological arousal

James famously illustrated this assertion with a story of a man being chased by a bear. A man is unfortunate enough to encounter a bear in a forest. He is afraid and, naturally, his heart races and he is sweating as he starts running away. According to the psychologist, it is precisely these physiological changes that provoke the man’s feeling of fear. In other words, he doesn’t run from the bear because he is afraid. He is afraid because of his physiological response to running away. 

Fritz Strack’s cartoon experiment

In 1988, German psychologist Fritz Strack and his colleagues conducted a well-known experiment to demonstrate the facial feedback hypothesis. The participants in Strack’s experiment were instructed to look at cartoons and say how funny they thought these cartoons were. They were asked to do this while holding a pen in their mouths. Some participants held the pen with their lips, which pushed the face into a frown-like expression. Others held it with their teeth, forcing a smile. 

Strack’s results were in line with the facial feedback hypothesis and were since confirmed by several other studies. The participants who used a pen to mimic a smile thought that the cartoons were funnier than those who were frowning. The participants’ emotions were clearly influenced by their facial expressions. 

Characteristics of Facial Feedback

The brain is hardwired to use the facial muscles in specific ways in order to reflect emotions. When contracted, facial muscles pull on the skin allowing us to produce countless expressions ranging from frowning to smiling, raising an eyebrow, and winking. In fact, we are capable of making thousands of different facial expressions, each one lasting anywhere between ​ 0.5 seconds (microexpressions) to 4 seconds. 

universal expressions

But facial expressions can indicate various degrees of emotions as well. When we are slightly angry, we display only a light frown and somewhat furrowed eyebrows. If we are furious, our expression becomes more distinctive. In addition, we can show combinations of different emotions through subtle variations of our facial movements.

The facial feedback hypothesis has the strongest effect when it comes to modulation, that is, intensifying our existing feelings rather than initiating a completely new emotion. 

Modulating also means that if we avoid showing our emotions using our facial muscles we will, as a consequence, experience a weaker emotional response. We won’t feel the emotions as strongly as we otherwise would. The lack of facial expressions or inhibition of these expressions lead to the suppression of our emotional states. 

Applications of the Facial Feedback Hypothesis

The facial feedback phenomenon has several possible applications. It can help us be more positive, have better control of our emotions, and strengthen our feelings of empathy. We can simply use the facial feedback hypothesis to make us feel better in situations that we would rather avoid. If we force a smile instead of frowning at a boring event, for example, we may actually start to enjoy ourselves a bit more. We can use the same exercise whenever we are feeling overwhelmed, powerless, or stressed. 

Research shows that regulating emotions through facial feedback can have positive outcomes in areas ranging from psychotherapy to child education and endurance performances.

Related posts:

  • Paul Ekman Biography - Contributions To Psychology
  • Body Language Basics - How to Read Someone
  • Facial Expressions of Emotions (Microexpressions)
  • James-Lange Theory of Emotion (Definition + Examples)
  • Two Factor Theory of Emotion

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What Is The Facial Feedback Hypothesis And Does It Work?

Emotions are a basic part of the human experience, and expressing those emotions appropriately can be a part of improving one’s mental health. We can show our emotions in many ways, but one of the quickest and most common ways is through facial expressions. Facial expressions can do more than show others how we feel. Scientists have proposed the facial feedback hypothesis, which suggests that changing our facial expressions can also change our emotions.

What Is The Facial Feedback Hypothesis?

The  facial feedback hypothesis  states that our facial expressions affect our emotions. If the facial-feedback hypothesis is correct, then not only do we smile when we feel happy, but smiling can make us feel happy, too. According to this hypothesis, in these cases, it is the act of smiling that produces a happy feeling. The same might hold true for other emotions as well.

Background Of The Hypothesis

Scientists have been interested in the idea of a facial-feedback hypothesis since the 1800s. In the 1840s, William James presented the idea that awareness of your bodily experiences is the basis of emotion. Thus, if you know that certain facial expressions are the ones you associate with being sad, you may experience a feeling of sadness.

Darwin investigated the way animals used facial expressions and suggested the idea of facial feedback in the 1870s. Through the latter half of the 1900s, the topic of facial feedback became popular again. Since then, many different studies have been done to test this hypothesis.

Types Of Facial Expressions

What types of facial expressions can produce the emotions we feel? The scientific community is still debating how the facial feedback hypothesis might work with different expressions. One thing that seems certain, though, is that a smile is connected to the production of a happy emotion, while a frown is connected to a feeling of sadness.

Basic Emotions

Degrees of emotions.

Along with the type of emotion we feel, we can also show the degree of that emotion through our facial expressions. For example, you may be slightly angry and express that emotion with a slight frown and furrowed eyebrows. If you're furious, though, your expressions will likely be much more distinctive.

Complex Emotions

Often, we may feel combinations of emotions. Emotions aren't always pure or easily defined. Some common complex emotions are joyful love, prideful anger, and ambivalence. Complex emotions can be expressed with subtle variations of the usual facial expressions.

Duchenne Vs. Non-Duchenne Smiles

A Duchenne smile is a  genuine smile , while a non-Duchenne smile is a fake smile. Although these two types of smiles are differentiated by whether the smile expresses an honest emotion you're feeling, you can make either expression whether you're already feeling happy or not.

In the non-Duchenne smile, you simply raise the corners of your mouth. It's what you might do when someone is going to take a photograph of you. They say, “Say cheese,” and you comply with a non-Duchenne smile.

The Duchenne smile starts with that same facial contraction, but it also involves raising your cheeks and squeezing your eyes. Your involuntary muscles do the extra work. So, how can you produce a Duchenne smile if you can't actively control those muscles? If we know what a Duchenne smile looks like, most of us can produce the same expression.

In a 2019 study, scientists carried out two experiments around Duchenne and non-Duchenne smiling. One evaluated how ostracism influenced the expression of emotion in a social environment, while the second replicated the results of the first experiment but focused particularly on smiling and self-reported emotion. In the first experiment, the participants who had higher frequencies of Duchenne smiling even during exclusion from the conversation self-reported higher rates of happiness. In the second, the relationship between non-Duchenne smiling and self-reported happiness was negative. However, certain participants were able to control their own emotional experience even while being ostracized, which led to an unexpected up-regulation of positive emotions .

Individual And Cultural Differences

Although all humans have many of the same basic facial expressions, some expressions may be unique to a specific individual or culture. So, if you know the person or culture well, it may be easier to understand what someone is expressing through facial expressions.

How The Facial Muscles Express Emotions

We often express emotions in our bodies, especially by using our facial muscles in specific ways. Why do we do it? How do we know how to hold our faces to show our emotions? The answers are both biological and cultural.

Facial Expressions Are Hardwired In The Brain

Scientists believe that our brains are  hardwired  to use the facial muscles in specific ways to show our emotions. They suggest that this developed because people needed to live in groups to survive. This neurological phenomenon happens not only in people who can see and imitate the expressions of others but also in people who were born blind.

Facial Expressions Are Both Instinctual And Learned

Our expressions are instinctual, but we can also learn them from others. Did you ever notice a child's smile that looked identical to a parent's smile? That can happen not only between biological parents and children but also between parents and their adopted children. It's because they tend to imitate their parents’ expressions.

Along with imitating our relatives, we tend to watch others in our culture to learn how to express our emotions. We may meet others in person, watch them on a television show or YouTube video, or see their expression in a photo. When we do, we instinctually understand what they're expressing, and we can learn to express that emotion in the same way.

Which Comes First: The Expression Or The Feeling?

We tend to think it's our emotions that determine our facial expressions. However, the facial-feedback hypothesis states that expression can work in the opposite direction. That is, the way we contract our facial muscles may generate emotional feelings within us. The question of whether that happens is still the subject of research studies.

What Does the Facial-Feedback Hypothesis Mean To Me?

How our expressions influence our emotions may pose some interesting questions, but does it have any practical applications? If the facial-feedback hypothesis is true, as research up to the present seems to indicate, there may be several ways to take advantage of the phenomenon. Researchers have found that facial feedback appears to happen during the movement of facial muscles to create expressions, which attenuates ongoing feelings and emotions.

Enjoy Life More

Do you ever find yourself in a situation you'd rather avoid? Perhaps you have to be in class or at work when you'd rather be outside enjoying a beautiful day. Maybe you need to interact socially to advance your career or promote your favorite cause, but you'd rather spend the time alone.

If you apply the facial feedback hypothesis in these situations, you might find that you enjoy your time even if you're doing something you'd rather not do. As you smile, happy feelings may follow, allowing you to enjoy these moments wherever you are.

Avoid Negative Emotions More Often

If facial feedback can also cause negative emotions, you may be able to mitigate these feelings or feel them less frequently. If you don't want to feel unhappy, you may try to avoid frowning. If you don’t want to feel angry, you may decide to stop clenching your teeth and decide to modify your expression. If the theory is correct, unpleasant feelings may be far less troublesome.

Have More Understanding And Control Over Emotions

It can be healthy and mature to acknowledge your present feelings without wholly giving in to them. You may be able to control distressing emotions, which can improve your mental health. That doesn't mean you never show emotions spontaneously, but you have other options when you need them.

If your emotions sometimes make you feel overwhelmed, facial feedback may help. You can learn valuable techniques from a counselor during online therapy. Aside from teaching you new techniques for controlling your emotions, therapy may help you explore the issues behind those emotions and address any underlying problems.

Online Therapy Can Support You

If you’re thinking about your next steps, online therapy may help you explore your concerns under the guidance of an experienced, licensed counselor. A 2018 study published in the Journal of Anxiety Disorders found that online therapy was equally as effective as traditional in-person counseling; 80% of the trials conducted on computer-delivered therapy sessions saw more than half of the participants showing high rates of satisfaction.

When you choose  online counseling , you can work with a licensed counselor that you choose among thousands of counselors. You can select a therapist who addresses the same types of emotional challenges you're facing, whether you're experiencing anger, sadness, anxiety, or another emotion.

You can also choose a counselor for the type of therapy they offer, whether cognitive behavioral therapy, existential therapy, or dialectical behavior therapy. Their specialties, experience, and educational backgrounds are available for you to read and assess before you set up your first appointment.

Therapist Reviews

“Sharon helps you discuss your struggles then somehow knows the exact words to inspire action. She has helped immensely with my negative self-talk and has brought up my self esteem a lot.”

“Her guidance throughout this process of change has helped tremendously. When I get off the phone I feel a sense of release of what was clouding my mind. I have tendencies to have negative thoughts and with the techniques she has brought to my attention I’ve been able to redirect my thoughts to a reality based point of view. It’s been two weeks and I feel my path with counseling has made an impact already.”

What is the facial feedback hypothesis?

The facial feedback hypothesis is the theory that facial expressions can activate and regulate emotions by influencing the processing of emotional stimuli. By smiling when you’re happy, this hypothesis suggests that you will feel happier. Or, by furrowing your brow when you’re angry, you may feel angrier. This concept was first introduced by Charles Darwin in 1872, but it did not become popular until the 1980s, when the facial feedback hypothesis was defined in the Journal of Personality and Social Psychology . It has since received both criticism and praise as more research is conducted to test this hypothesis. 

What does facial feedback suggest?

Most people believe that we smile when we’re happy, or frown when we’re sad. However, according to the facial feedback hypothesis, the inverse could be true. This would suggest that smiling could cause happiness, and angry facial expressions could cause anger. 

What is the facial feedback hypothesis proposed by James-Lange?

William James and Carl Lange developed the James-Lange Theory of Emotion. According to this theory, physiological changes trigger emotions. For example, if you encountered a rabid dog, your heart rate would rise and you may start perspiring and running away from the dog. James and Lange propose that these physiological changes trigger the emotion and expression of fear, rather than fear triggering the physiological response. Simply put, James and Lange would say you feel afraid because your heart rate has risen, rather than your heart rate rising because you feel afraid. 

The James-Lange Theory has received significant criticism. For example, this theory does not explain why people with limited physiological responses or reduced sensations still experience emotions. 

What is the facial feedback hypothesis of Charles Darwin?

The first of several facial feedback hypotheses was introduced by Charles Dawin in 1872, when he proposed that emotional facial expressions are ubiquitous and innate (not socially learned) in his book, The Expression of the Emotions in Man and Animals. In this book, Darwin observed that emotions intensified when facial muscle regions were engaged , and softened when facial responses were repressed. 

William James and Carl Lange later built on this theory, developing the James-Lange Theory that facial expressions and other physiologic changes generate emotional states.

What is the facial feedback hypothesis replication crisis?

When scientists ask research participants to adopt a voluntary facial action (i.e., by instructing participants to smile or frown), they can unintentionally skew study results. To address this concern, a 1988 study used pens to manipulate facial expression by having participants hold a pen between their teeth or lips, thus inducing smiling or frowning without participant awareness. The researchers then had participants look at a series of cartoons, and found that “smiling” participants reported more positive emotions and found the cartoons more amusing. However, other studies have failed to replicate these results . 

In 17 separate direct replications of the 1988 study , results indicated no significant difference between the “smile” and “frown” groups. 

What are the benefits of facial feedback?

If true, the facial feedback phenomenon suggests that you may feel happier simply by smiling. Therefore, if you’re feeling down, you could boost your mood by reminding yourself to smile. Many people support the notion that “faking it till you make it,” or “turning your frown upside down,” can make you happier. 

However, there is mixed support for the facial feedback hypothesis. Additionally, forcing yourself to disingenuously smile may have a negative impact on your wellbeing. One study found that service workers who felt obligated to smile while interacting with customers experienced heightened rates of excessive alcohol consumption . 

Finally, there have been debates about what nonverbal behaviors, like smiling, actually communicate. While some social psychologists believe that smiling is an expression of happiness, others believe it’s used as a form of social influence to indicate willingness to cooperate with others. 

How has facial feedback effect been supported?

There has been mixed evidence regarding the facial feedback effect. For example, researchers have used the voluntary facial action technique to test the facial feedback hypothesis, instructing participants to induce frowns or smiles in response to positive and negative stimuli, and then rate the pleasantness. They found that facial expressions can reduce the intensity of emotional states , but this effect is generally only present during the actual facial action.

A large 2019 meta-review examined 50 years of research, including 286 studies, found that altering facial expressions has a very small or nonexistent effect on mood . On average, if 100 people smiled, seven may feel happier than they would without smiling .

What best explains the facial feedback effect?

Facial feedback literature was widely popular in the 1980s and 1990s, with particular focus on the vascular theory of facial efference. This theory proposes that facial feedback effects occur when the facial muscles are activated, which may regulate cerebral blood flow and therefore influence emotions . 

How does Botox relate to the facial feedback hypothesis?

Botulinum toxin (Botox) is often injected into the upper region of the face, where it can reduce dynamic creases utilized in some expressive behaviors, such as anger and shock. Some doctors believe that Botox injections could limit the ability to frown , and thus may reduce negative facial feedback effects, leading to more positive emotional states overall. 

What is the facial feedback hypothesis on Quizlet?

By creating a free Quizlet account, you can review user-generated study questions and flashcards that cover the facial feedback hypothesis and other psychology concepts . 

Exploring The Different Types Of Humor And Their Effects On Personalities

What are alpha brain waves, seeking to improve your mental health, top categories.

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IResearchNet

Facial-Feedback Hypothesis

The facial-feedback hypothesis states that the contractions of the facial muscles may not only communicate what a person feels to others but also to the person him- or herself. In other words, facial expressions are believed to have a direct influence on the experience of affect. This hypothesis goes back to Charles Darwin, who wrote that the expression of an emotion intensifies it, whereas its repression softens it. A second origin of the facial-feedback hypothesis is William James’s theory of emotion, which states that the bodily changes follow the perception of an exciting fact and that the feeling of these bodily changes is the emotion.

Facial-Feedback Hypothesis

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To test the causal influence of facial expressions on the experience of affect, three different procedures have been employed. In some experiments, participants were explicitly instructed to adopt an emotionally relevant facial expression. In another set of studies, the emotional meaning of the expression was not mentioned. Instead, the experimenter would point at the muscles that were supposed to be contracted. In yet a third method, facial expressions were induced by a procedure that required the contraction of specific muscles for a purpose that was void of any emotional meaning. For example, participants were told to hold a pen with either their teeth or their protruded lips to either induce or inhibit a smiling expression by extracting the zygomaticus muscle (one of the main muscles involved in making the mouth into a smile) or its antagonist. In a related study, golf tees were fixed on people’s foreheads, which they had to move together by contracting the corrugator (frowning) muscle.

All procedures were successful in causing affective consequences either in people’s self-reported mood, in specific emotions, or in the evaluation of emotional stimuli, like cartoons. However, the three facial-induction methods afford different theoretical interpretations. Specifically, the more likely it is that the induction of the facial expression is linked to the recognition of its emotional meaning, the more likely it is that people may infer their affective state on the basis of their expression. For example, they may draw the inference that if they smile, they must be amused. This mechanism is an extension of Bem’s self-perception theory, which assumes that if internal cues are weak or ambiguous, people infer their attitudes from their behavior. Similarly, they may infer their emotional states from what they do. However, the fact that affective consequences can be obtained from facial expressions even if their emotional meaning is disguised suggests that more direct mechanisms may be operating as well.

While self-perception theory may account for the cases in which the meaning of the expressions is apparent, other models are necessary to explain the direct impact of the facial action. On a physiological level, it has been argued that facial expressions may regulate the volume and particularly the temperature of the blood that flows to the brain and therefore influence cerebral processes. It was suggested that an emotional event may cause peripheral muscular, glandular, or vascular action that changes the emotional experience. Another explanation that is based on evidence from the neurosciences comes from a study that identifies specific cortical activities that are connected to different facial expressions. Specifically, it was found that the facial expression of emotions that are linked to approach (e.g., joy) were associated with greater left frontal brain activity while avoidance emotions (e.g., fear and anger) were linked with greater right frontal activation.

From a more psychological perspective, the effects of facial feedback can be understood as the result of a motivational orientation. As an example, one theory assumes that behaviors that are involved in approach facilitate the processing of positive information, whereas behaviors that are involved in avoidance facilitate the processing of negative information. Applied to facial expressions, this implies that a smiling expression will facilitate the processing of a cartoon and therefore intensify its affective impact. This also explains why, in many studies, the mere adoption of an expression has by itself had no emotional effect.

The importance of facial feedback has been recognized in domains that go beyond the emotional experiences. For example, it has been found that positive or negative sentences are understood more easily if, outside of their awareness, people were led to adopt a facial expression that corresponded to the valence of the sentence. In one study, research participants had to hold a pen in the smiling pose while watching photos of either White or Black people. As a consequence, implicit racial bias was reduced. Also, the importance of facial feedback has been recognized as a mediator of empathy and prosocial behavior.

Finally, it should be noted that certain facial expressions require effort to be maintained, which may influence the experienced fluency in information processing. The experience of fluency was found to serve as a basis for other feelings and judgments, like those of familiarity and fame. For example, it has been found that judgments of fame are often based on the feeling of familiarity that is elicited by a name. More recently, it was demonstrated that having participants furrow the brow while reading the names reduced the fame that was associated with the names. This was presumably the case because the experienced effort undermined the feelings of familiarity and, as a consequence, the judged fame.

References:

  • Laird, J. D. (1974). Self-attribution of emotion: The effects of expressive behavior on the quality of emotional experience. Journal of Personality and Social Psychology, 29, 475-486.
  • Strack, F., Martin, L. L., & Stepper, S. (1988). Inhibiting and facilitating conditions of the human smile: A nonobtrusive test of the facial feedback hypothesis. Journal of Personality and Social Psychology, 54, 786-777.
  • Zajonc, R. (1989). Feeling and facial efference: Implications of the vascular theory of emotion. Psychological Review, 39, 117-124.

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A multi-lab test of the facial feedback hypothesis by the Many Smiles Collaboration

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Nature Human Behaviour volume  6 ,  pages 1731–1742 ( 2022 ) Cite this article

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Following theories of emotional embodiment, the facial feedback hypothesis suggests that individuals’ subjective experiences of emotion are influenced by their facial expressions. However, evidence for this hypothesis has been mixed. We thus formed a global adversarial collaboration and carried out a preregistered, multicentre study designed to specify and test the conditions that should most reliably produce facial feedback effects. Data from n  = 3,878 participants spanning 19 countries indicated that a facial mimicry and voluntary facial action task could both amplify and initiate feelings of happiness. However, evidence of facial feedback effects was less conclusive when facial feedback was manipulated unobtrusively via a pen-in-mouth task.

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Large-scale citizen science reveals predictors of sensorimotor adaptation

Jonathan S. Tsay, Hrach Asmerian, … Ken Nakayama

The facial feedback hypothesis suggests that individuals’ emotional experiences are influenced by their facial expressions. For example, smiling should typically make individuals feel happier, and frowning should make them feel sadder. Researchers suggest that these effects emerge because facial expressions provide sensorimotor feedback that contributes to the sensation of an emotion 1 , 2 , serves as a cue that individuals use to make sense of ongoing emotional feelings 3 , 4 , influences other emotion-related bodily responses 5 , 6 and/or influences the processing of emotional stimuli 7 , 8 . This facial feedback hypothesis is notable because it supports broader theories that contend emotional experience is influenced by feedback from the peripheral nervous system 9 , 10 , 11 , as opposed to experience and bodily sensations being independent components of an emotion response 12 , 13 , 14 . Furthermore, this hypothesis supports claims that facial feedback interventions—for example, smiling more or frowning less—can help manage distress 15 , 16 , improve well-being 17 , 18 and reduce depression 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 .

Recently, a collaboration involving 17 independent teams consistently failed to replicate a seminal demonstration of facial feedback effects 40 . In the original study, the participants viewed humorous cartoons while holding a pen in their mouth in a manner that either elicited smiling (pen held in teeth) or prevented smiling (pen held by lips) 41 . Consistent with the facial feedback hypothesis, smiling participants reported feeling more amused by the cartoons. This finding was influential because previous studies often explicitly instructed participants to pose a facial expression, raising concerns about demand characteristics 42 , 43 , 44 . Furthermore, theorists disagreed about whether these effects could occur outside of awareness 45 , 46 , 47 . Because the participants in this pen-in-mouth study were presumably unaware that they were smiling, the authors concluded that facial feedback effects were not driven by demand characteristics and could occur outside of awareness.

What implications does the failure to replicate have for the facial feedback hypothesis? One possibility is that the facial feedback hypothesis is false. However, this conclusion is unwarranted because this direct replication was limited to a specific test of the facial feedback hypothesis. Indeed, the replicators stated that their findings “do not invalidate the more general facial feedback hypothesis” 40 . Similarly, while arguing that the pen-in-mouth effect is unreliable, some researchers conceded that “other paradigms may produce replicable results” 48 .

A second possibility is that both the facial feedback hypothesis and the original pen-in-mouth effect are true. If this is the case, researchers must determine why others were unable to replicate the pen-in-mouth effect. One suggestion is that the replicators did not perform a true direct replication because they deviated from the original study by overtly recording the participants (per the advice of an expert reviewer) 49 . According to this explanation, awareness of video recording may induce a self-focus that interferes with participants’ internal experiences and emotional behaviour 49 , 50 .

A third possibility is that the facial feedback hypothesis is true, but not in the context examined in the original pen-in-mouth study. Perhaps facial feedback effects occur only when participants are aware that they are posing a facial expression 45 , 46 , a mechanism that the pen-in-mouth task was designed to eliminate. Alternatively, perhaps the pen-in-mouth task is not a reliable manipulation of facial feedback. Some theorists predict that facial feedback effects will emerge only when facial movement patterns resemble a prototypical emotional facial expression 5 , 51 , 52 , 53 , 54 , 55 , and previous research indicates that the pen-in-mouth task does not reliably produce prototypical expressions of happiness 56 . Last, perhaps facial feedback influences only certain types of emotional experiences. Some researchers distinguish between self-focused and world-focused emotional experiences, and facial feedback theories have traditionally emphasized self-focused emotional experience 57 , 58 . However, in the original pen-in-mouth study, the participants were asked how amused a series of cartoons made them feel, which may have induced a world-focused emotional experience.

Amid the uncertainty created by the failure to replicate, a meta-analysis was performed on 286 effect sizes from 137 studies testing the effects of various facial feedback manipulations on emotional experience 59 . The results indicated that facial feedback has a small but highly varied effect on emotional experience. Notably, this effect could not be explained by publication bias. Published and unpublished studies yielded effects of similar magnitude, analyses failed to uncover significant evidence of publication bias and bias-corrected overall effect size estimates were significant. However, this meta-analysis did not explain why facial feedback effects were not observed in the pen-in-mouth replication study. Inconsistent with preliminary evidence that video-recording awareness interferes with facial feedback effects 50 , the meta-analysis revealed significant facial feedback effects regardless of whether studies used overt video recording 59 .

Although the meta-analysis suggests that the facial feedback hypothesis is valid, there are at least three limitations that could undermine this conclusion. First, since publication bias analyses often have low power 60 , 61 , 62 , it is possible that seemingly robust facial feedback effects are driven by studies with undetected questionable research practices. Second, it is possible that the overall effect size estimates in this literature are driven by low-quality studies 63 . Third, even relatively similar subsets of facial feedback studies varied beyond what would be expected from sampling error alone, meaning that moderator analyses had lower power and potentially contained unidentified confounds. Consequently, the meta-analysis could not reliably identify moderators that may help explain why some researchers fail to observe facial feedback effects.

Both the failure to replicate the pen-in-mouth study and the meta-analysis have a unique set of limitations that make it difficult to resolve the debate regarding whether the facial feedback hypothesis is valid. We therefore came together to form the Many Smiles Collaboration. We are an international group of researchers—some advocates of the facial feedback hypothesis, some critics and some without strong beliefs—who collaborated to (1) specify our beliefs regarding when facial feedback effects, if real, should most reliably emerge; (2) determine the best way(s) to test those beliefs; and (3) use this information to design and execute an international multi-lab experiment.

We agreed that one of the simplest necessary conditions for facial feedback effects to emerge is that participants pose an emotional facial expression and subsequently self-report the degree to which they are experiencing the associated emotional state. Therefore, our main research question was whether participants would report feeling happier when posing happy versus neutral expressions. On the basis of outstanding theoretical disagreements in the facial feedback literature, we also questioned (1) whether happy facial poses only influence feelings of happiness if they resemble a natural expression of happiness, (2) whether facial poses can initiate emotional experience in otherwise neutral scenarios or only amplify ongoing emotional experiences, and (3) whether facial feedback effects are eliminated when controlling for awareness of the experimental hypothesis. These disagreements ultimately informed the final experimental design: a 2 (Pose: happy or neutral) × 3 (Facial Movement Task: facial mimicry, voluntary facial action or pen-in-mouth) × 2 (Stimuli Presence: present or absent) design, with Pose manipulated within participants and Facial Movement Task and Stimuli Presence manipulated between participants (Supplementary Fig. 1 ).

To provide an easy-to-follow task that would produce more prototypical facial expressions, we used a facial mimicry paradigm, wherein the participants were asked to mimic images of actors displaying prototypical expressions of happiness 64 . To produce less prototypical facial expressions, some participants completed the voluntary facial action task 65 , wherein they were asked to move some—but not all—facial muscles associated with prototypical expressions of happiness 56 . We also added the pen-in-mouth task after Stage 1 reviewer feedback, wherein the participants held a pen in their mouth in a manner that either elicited smiling (pen held in teeth) or prevented smiling (pen held by lips) 41 . While engaging in the facial feedback tasks, half of the participants viewed a series of positive images 57 , 58 .

We hypothesized that participants would report experiencing more happiness when posing happy versus neutral facial expressions. Furthermore, we hypothesized that the magnitude of this effect would be similar across tasks that produce less (the voluntary facial action and pen-in-mouth tasks) versus more (the mimicry task) prototypical expressions of happiness. We also expected that facial feedback effects would be smaller in the absence than in the presence of positive stimuli. Last, we expected to observe facial feedback effects even when limiting our analyses to participants who were completely unaware of our hypothesis. Two pilot studies ( n  = 206; Supplementary Information ) confirmed these predictions. A third pilot study conducted after initial Stage 1 acceptance ( n  = 119; Supplementary Information ) provided preliminary evidence in favour of some—but not all—of our predictions. These pilot results led to minor refinements to the methodology but did not change our final set of predictions. Our research questions and hypotheses are summarized in Table 1 .

We conducted all analyses using R (v.4.1.2) 66 . For the frequentist analyses, we fit mixed-effect models using the lme4 package 67 . Some of these models contained random slopes and thus have smaller degrees of freedom. For tests of main effects, simple effects and interactions, we used the lmerTest package to derive analysis-of-variance-like F values with Satterthwaite degrees of freedom 68 . When we observed higher-order interactions, we used the emmeans package to decompose them using simple effect tests and pairwise contrasts 69 . We used model-derived mean difference estimates as our effect size of interest. However, we also report semi-standardized mean difference estimates, wherein the model-derived mean difference is divided by the total range of the measured dependent variable.

For the Bayesian re-analysis of the hypotheses in Table 1 , we used the BayesFactor package to fit models using medium Cauchy priors ( r scale, 1/2) on the alternative hypotheses and the default Markov chain Monte Carlo settings 70 . We also performed sensitivity analyses with wide ( r scale, √2/2) and ultrawide ( r scale, 1) priors, and we thus report a range of Bayes factors (BFs). For tests of main effects, interactions and simple effects, we computed BFs by comparing models containing versus excluding the terms representing the tested effect.

Participants

We made two minor deviations from the preregistered sampling plan. First, due to constraints created by COVID-19, no research group collected data in person. We were thus unable to test whether our pattern of results differed by in-person versus online data collection. Second, we had 80 fewer participants than we initially planned for our primary analyses.

Depending on the research site, the participants completed the study on a completely volunteer basis, for partial course credit, for extra credit, for entrance into a lottery (for example, for a gift box), for a prize (for example, a pen) or for money (US$0.75–US$5). We stopped data collection when at least 22 research groups had each collected at least 105 participants, totalling 3,878 participants from 26 groups (Fig. 1 ; mean age ( M age ), 26.6; s.d. age , 10.6; 71% women, 28% men, 1% other). For the primary analyses, we excluded participants if they failed an attention check (17% fail rate), completed the study on a mobile device (3%), reported deviating from the pose instructions (1%), reported that their posed expression did not match an image of an actor completing the task correctly (3%), indicated that they were very distracted (3%) or exhibited any awareness of the study hypothesis (46%). (For the country-specific exclusion criteria rates, see the Supplementary Information .) An unexpectedly large number of participants were excluded for exhibiting awareness of the study hypothesis—but this may reflect an unusually strict classification scheme (that is, that two coders must judge the participant as being completely unaware). This left 1,504 participants for the primary analyses.

figure 1

Data were collected from 3,878 participants in 19 countries. Darker shades of red denote larger country-specific sample sizes.

Source data

Primary analyses.

We hypothesized that participants would report higher levels of happiness (1) in the presence versus absence of emotional stimuli and (2) after posing happy versus neutral facial expressions. We also predicted that the effect of posed expressions on happiness would be larger in the presence than in the absence of positive stimuli. Following the study design (Supplementary Fig. 1 ), we modelled happiness reports with (1) Pose (happy or neutral), Facial Movement Task (facial mimicry, voluntary facial action or pen-in-mouth) and Stimuli Presence (present or absent) entered as effect-coded factors; (2) all higher-order interactions; (3) random intercepts for participants and research groups; and (4) random slopes for research groups.

Participants reported higher levels of happiness in the presence than in the absence of positive images ( M diff  = 0.30; 95% confidence interval (CI), (0.12, 0.48); 5% scale range; F (1, 22.65) = 10.67; P  = 0.003). However, the Bayesian analyses were inconclusive (BF 10  = 0.71–1.25). Participants also reported more happiness after posing happy versus neutral expressions ( M diff  = 0.31; 95% CI, (0.21, 0.40); 5.17% scale range; F (1, 24.34) = 39.86; P  < 0.001; BF 10  = 61.06–102.63. Contrary to our hypothesis, the Pose effect was not significantly larger in the presence than in the absence of positive stimuli ( F (1, 29.50) = 1.33, P  = 0.26, BF 10  = 0.06–0.13).

Unexpectedly, there was an interaction between Pose and Facial Movement Task ( F (2, 32.95) = 17.11, P  < 0.001, BF 10  = 34.13–100.14, Fig. 2 ). The effect of Pose on self-reported happiness was the largest in the facial mimicry task ( M diff  = 0.49; 95% CI, (0.36, 0.61); 8.17% scale range; F (1, 28.62) = 57.55; P  < 0.001; BF 10  > 100) and the voluntary facial action task ( M diff  = 0.40; 95% CI, (0.23, 0.56); 6.67% scale range; F (1, 25.48) = 22.93; P  < 0.001; BF 10  = 25.20–39.26). There was moderate support for the null hypothesis in the pen-in-mouth condition ( M diff  = 0.04; 95% CI, (−0.07, 0.15); 0.67% scale range; F (1, 24.74) = 0.57; P  = 0.46; BF 10  = 0.11–0.17.

figure 2

Self-reported happiness (1 = ‘not at all’ to 7 = ‘an extreme amount’) after the participants posed happy facial expressions, posed neutral facial expressions or completed filler tasks. The panel columns indicate whether the participants completed the facial mimicry, voluntary facial action or pen-in-mouth task. The panel rows indicate whether positive images were absent or present during the facial pose tasks. The grey points represent jittered participant observations. The blue error bars represent mean ± 1 standard error. Condition-specific sample sizes, means and standard deviations are reported.

Secondary analyses

Our secondary analyses were designed to further probe the nature of facial feedback effects.

Potential aversion to the neutral expression posing task

The primary analyses suggest that posing happy versus natural expressions can increase feelings of happiness. However, an alternative explanation is that these effects are driven by hypothesis-irrelevant decreases in happiness after neutral poses (for example, as a result of boredom) 71 . To test this, we refit the primary analysis model with an effect-coded Pose factor that compared happy pose with filler trials that the participants completed. We focused on participants who were not exposed to positive images because these images were shown only during the facial posing trials (thus confounding their comparison with the filler trials). Nevertheless, similar results were observed in analyses that included participants who viewed positive images (Fig. 2 ).

Like the primary analyses, there was an interaction between Pose and Facial Movement Task ( F (2, 18.02) = 20.47, P  < 0.001). Participants reported higher levels of happiness after posing happy expressions versus completing filler tasks in both the facial mimicry task ( M diff  = 0.48; 95% CI, (0.29, 0.67); 8% scale range; t (22.4) = 5.23; P  < 0.001) and the voluntary facial action task ( M diff  = 0.20; 95% CI, (0.05, 0.36); 3.33% scale range; t (19.6) = 2.69; P  = 0.01. In the pen-in-mouth task, participants reported less happiness after completing the happy versus filler task ( M diff  = −0.15; 95% CI, (−0.28, 0.02); 2.5% scale range; t (31.5) = 2.39; P  = 0.02).

Moderating role of pose quality

We next examined the moderating role of three indicators of the quality of posed expressions: the participants’ reports of the extent to which they followed pose instructions (compliance ratings), felt that their self-monitored expression matched an image of an actor successfully completing the task (similarity ratings) and felt that their posed expression resembled a genuine expression of happiness (genuineness ratings). For each quality indicator, we refit the primary analysis model with (1) the indicator entered mean-centred and (2) a term denoting its interaction with Pose. For each quality indicator, there was an interaction with Pose (Fig. 3 ). The effect of facial poses on happiness was larger among participants with higher compliance ( β  = 0.08; 95% CI, (0.05, 0.12); t (1,482.63) = 4.33; P  < 0.001), similarity ( β  = 0.03; 95% CI, (0.01, 0.06); t (1,358.62) = 3.37; P  < 0.001) and genuineness ratings ( β  = 0.08; 95% CI, (0.06, 0.09); t (1,420.95) = 10.57; P  < 0.001).

figure 3

The change in happiness ( y axis) when the participants posed happy versus neutral expressions was moderated by compliance, similarity, genuineness and hypothesis awareness ratings, but not body awareness ratings ( x axes). The grey points represent jittered participant observations. The blue lines represent the estimated linear relationships.

Pose quality in different facial movement tasks

To examine whether pose quality varied between facial movement tasks, we used data from all 3,878 participants and modelled each quality indicator with (1) Facial Movement Task and Stimuli Presence entered as effect-coded factors, (2) random intercepts for research groups and (3) random slopes for research groups.

Compliance ratings varied by Facial Movement Task ( F (2, 18.18) = 10.50, P  < 0.001), but not Stimuli Presence ( M diff  = 0.03; 95% CI, (−0.05, 0.11); 0.5% scale range; F (1, 37.63) = 0.60; P  = 0.44). Compliance ratings were high across all tasks, but slightly lower in the facial mimicry task ( M  = 6.45, s.d. = 1.07) than in the voluntary facial action ( M  = 6.57; s.d. = 0.93; M diff  = −0.15; 95% CI, (−0.28, −0.02); 2.5% scale range; t (23.5) = −2.47; P  = 0.02) and pen-in-mouth tasks ( M  = 6.68; s.d. = 1.01; M diff  = −0.25; 95% CI, (−0.37, −0.14); 4.17% scale range; t (22.8) = −4.49; P  < 0.001). Compliance ratings were also slightly higher in the pen-in-mouth task than in the voluntary facial action task ( M diff  = 0.10; 95% CI, (−0.01, 0.21); 1.67% scale range; t (21.9) = 1.96; P  = 0.06).

Likewise, similarity ratings varied by Facial Movement Task ( F (2, 40.12) = 7.35, P  = 0.002), but not Stimuli Presence ( M diff  = −0.12; 95% CI, (−0.25, 0.02); 2% scale range; F (1, 19.18) = 3.15; P  = 0.09). Similarity ratings were high across all tasks but higher in the facial mimicry task ( M  = 5.30, s.d. = 1.36) than in the voluntary facial action ( M  = 5.09; s.d. = 1.73; M diff  = 0.23; 95% CI, (0.03, 0.43); 3.83% scale range; t (22.7) = 2.43; P  = 0.02) and pen-in-mouth tasks ( M  = 5.07; s.d. = 1.61; M diff  = 0.24; 95% CI, (0.11, 0.36); 4% scale range; t (194) = 3.63; P  < 0.001).

Genuineness ratings strongly varied by Facial Movement Task ( F (2, 13.69) = 82.56, P  < 0.001). Genuineness ratings were substantially lower in the pen-in-mouth task ( M  = 2.98, s.d. = 1.89) than in the facial mimicry ( M  = 4.15; s.d. = 1.92; M diff  = −1.15; 95% CI, (−1.34, −0.97); 19.17% scale range; t (23.85) = 12.85; P  < 0.001) and voluntary facial action tasks ( M  = 3.91; s.d. = 2.00; M diff  = −0.89; 95% CI, (−1.12, −0.66); 14.83% scale range; t (24.92) = 8.00; P  < 0.001). Genuineness ratings were also lower in the voluntary facial action task than in the facial mimicry task ( M diff  = −0.26; 95% CI, (−0.48, −0.05); 4.33% scale range; t (6.67) = −2.90; P  = 0.02). Participants also reported higher genuineness ratings in the presence ( M  = 3.78, s.d. = 2.00) than in the absence ( M  = 3.57, s.d. = 2.00) of positive images ( M diff  = 0.23; 95% CI, (0.11, 0.34); 3.83% scale range; F (1, 1,538.52) = 13.66; P  < 0.001).

Awareness of the study purpose

To examine whether some facial feedback tasks lead participants to be more aware of the study purpose, we used data from all 3,878 participants and modelled coder ratings of the extent to which they were aware with (1) Facial Movement Task and Stimuli Presence entered as effect-coded factors, (2) random intercepts for research groups and (3) random slopes for research groups. Awareness scores varied by Facial Movement Task ( F (2, 19.70) = 13.54, P  < 0.001), with participants being less aware in the pen-in-mouth task ( M  = 1.75, s.d. = 1.41) than in the voluntary facial action task ( M  = 2.28; s.d. = 1.78; M diff  = −0.48; 95% CI, (−0.67, −0.29); 8.02% scale range; t (24) = −5.19; P  < 0.001) and the facial mimicry task ( M  = 2.05; s.d. = 1.52; M diff  = −0.27; 95% CI, (−0.43, −0.11); 4.48% scale range; t (15.4) = −3.66; P  < 0.05). Participants were also less aware in the facial mimicry task than in the voluntary facial action task ( M diff  = −0.21; 95% CI, (−0.36, −0.07); 3.53% scale range; t (39.4) = −2.97; P  = 0.005).

To test whether facial feedback effects are amplified by awareness of the study purpose, we modelled happiness reports with (1) Pose, Facial Movement Task and Stimuli Presence entered as effect-coded factors; (2) awareness scores entered mean-centred; (3) a higher-order interaction term for Pose and awareness scores; (4) random intercepts for participants and research groups; and (5) research group random slopes for all terms other than awareness scores. The results indicated that the Pose effect was larger among participants who were more aware of the study hypothesis ( β  = 0.08; 95% CI, (0.06, 0.10); t (22.74) = 7.55; P  < 0.001) (Fig. 3 ).

Body awareness

To examine the moderating role of body awareness, we re-ran our primary analysis model with (1) participants’ responses on a body awareness measure entered mean-centred and (2) a higher-order interaction term for Pose and awareness. No moderating role of body awareness was detected ( β  = 0.00; 95% CI, (−0.03, 0.03); t (9.87) = 0.02; P  = 0.99) (Fig. 3 ).

Between-condition differences in other inclusion criteria

Next, we examined whether there were between-condition differences in the extent to which participants used an incorrect device to complete the study (for example, a phone) or failed attention checks. We separately modelled the probability that participants failed to meet each inclusion criterion using logistic mixed-effect regression with (1) Facial Movement Task and Stimuli Presence entered as effect-coded factors, (2) random intercepts for research groups and (3) random slopes for research groups.

The probability that participants used the incorrect device did not vary by Facial Movement Task (96%, 97% and 97% pass rates in the facial mimicry, voluntary facial action and pen-in-mouth tasks; χ 2 (2) = 3.06; P  = 0.22) or Stimuli Presence (97% pass rate in the absence and presence of positive stimuli; χ 2 (1) = 0.11; P  = 0.74). Likewise, the probability that participants failed attention checks did not vary by Facial Movement Task (84%, 82% and 83% pass rates in the facial mimicry, voluntary facial action and pen-in-mouth tasks; χ 2 (2) = 1.28; P  = 0.53) or Stimuli Presence (84% and 82% pass rates in the absence and presence of positive stimuli; χ 2 (1) = 2.54; P  = 0.11).

We also tested for between-condition differences in coder ratings of the extent to which participants were distracted using linear mixed-effect regression with (1) Facial Movement Task and Stimuli Presence entered as effect-coded factors, (2) random intercepts for research groups and (3) random slopes for research groups. Distraction scores did not significantly vary between the facial mimicry ( M  = 2.01, s.d. = 1.17), voluntary facial action ( M  = 1.92, s.d. = 1.14) and pen-in-mouth ( M  = 1.92, s.d. = 1.14) tasks ( F (2, 18.57) = 2.45, P  = 0.11). Distraction scores also did not vary in the absence ( M  = 1.94, s.d. = 1.15) versus presence ( M  = 1.96, s.d. = 1.16) of positive stimuli ( F (1, 900.52) = 0.02, P  = 0.90).

Anger and anxiety

We next examined whether posed happy expressions decreased self-reported negative emotions and whether some facial movement tasks were more frustrating and anxiety-provoking than others. To do so, we separately re-ran our primary analyses with anxiety and anger reports as the dependent variables.

Happy versus neutral facial expression poses did not significantly decrease feelings of anger ( M diff  = −0.02; 95% CI, (−0.07, 0.03); 0.33% scale range; F (1, 20.71) = 0.85; P  = 0.37) or anxiety ( M diff  = −0.01; 95% CI, (−0.06, 0.04); 0.17% scale range; F (1, 25.36) = 0.32; P  = 0.57). However, feelings of anger ( F (2, 27.46) = 4.30, P  = 0.02) and anxiety ( F (2, 58.20) = 5.18, P  = 0.008) did differ by Facial Movement Task. Participants reported higher levels of anger in the pen-in-mouth task than in the facial mimicry task ( M diff  = 0.14; 95% CI, (0.03, 0.24); 2.33% scale range; t (24.2) = 2.64; P  = 0.01) and the voluntary facial action task ( M diff  = 0.12; 95% CI, (0.02, 0.21); 2% scale range; t (31.6) = 2.40; P  = 0.02). Similarly, participants reported more anxiety in the pen-in-mouth task than in the facial mimicry task ( M diff  = 0.13; 95% CI, (0.02, 0.24); 2.17% scale range; t (51.6) = 2.35; P  = 0.02) and the voluntary facial action task ( M diff  = 0.17; 95% CI, (0.06, 0.28); 2.83% scale range; t (79) = 3.00; P  = 0.004). Nonetheless, follow-up exploratory analyses did not indicate that these increases in anxiety obfuscated facial feedback effects ( Supplementary Information ).

Exploratory analyses

For all analyses, we preregistered plans to model random slopes for research groups. However, random slopes often led to singular fit and convergence warnings, which is indicative of overfit models with potentially unreliable estimates 72 . Sensitivity analyses without (versus with) random slopes generally yielded identical inferences, except for the simple effect of Pose in the pen-in-mouth task. After we removed random slopes, the two-sided test of the effect of Pose was not significant ( M diff  = 0.08; 95% CI, (−0.01, 0.16); 1.33% scale range; F (1, 1,498) = 2.78; P  = 0.095), but an exploratory one-sided test was (one-sided P  < 0.05). However, the Bayesian analyses were inconclusive (BF 10  = 0.46–0.96). Nonetheless, when we relaxed our inclusion criteria in a subsequent sensitivity analysis, we found extremely strong evidence of a Pose effect in the pen-in-mouth task ( M diff  = 0.14; 95% CI, (0.07, 0.21); 2.33% scale range; F (1, 3,872) = 16.37; P  < 0.001; BF 10  > 100).

Our project brought together a large adversarial team to design and conduct an experiment that best tested and clarified our disagreements about the facial feedback hypothesis. We designed our experiment not to provide close replications of any existing study but rather to provide informative tests of the facial feedback hypothesis. For example, our pen-in-mouth task was inspired by the original pen-in-mouth study that some, but not all 49 , researchers have had difficulty replicating 40 . Nevertheless, our methodology differed in many ways from the original pen-in-mouth study. For example, we ran our study online (versus in person), focused on feelings of happiness (versus amusement), used a different cover story, had the participants pose expressions for a relatively short duration (five seconds) and did not instruct the participants to maintain the poses while they completed emotion ratings.

Our primary analyses replicated the pilot studies that informed the design of this study, albeit with more stringent inclusion criteria and a much larger and more culturally diverse sample (see Supplementary Fig. 2 for the country-specific effect size estimates). Contrary to theories that characterize peripheral nervous system activity and emotional experience as independent components of an emotion response 12 , 13 , 14 , our results suggest that facial feedback can impact feelings of happiness when using the facial mimicry and voluntary facial action tasks. Furthermore, these effects emerge in both the presence and absence of emotional stimuli—although, contrary to our prediction, the effect was not larger in the presence of emotional stimuli. Consistent with a previous meta-analysis, these results suggest that facial feedback can not only amplify ongoing feelings of happiness but also initiate feelings of happiness in otherwise neutral contexts 59 .

Secondary analyses revealed that the observed facial feedback effects could not be explained by participants’ aversion to the relatively inactive neutral pose task or demand characteristics. Even compared with relatively active filler trials, participants reported the most happiness after posing happy expressions. Furthermore, although facial feedback effects were larger among participants who were rated as more aware of the purpose of the study, we observed facial feedback effects among participants who did not exhibit such awareness. These results are consistent with recent experimental work demonstrating that demand characteristics can moderate, but do not fully account for, facial feedback effects 73 .

Consistent with our predictions and a previous meta-analysis 59 , facial feedback effects, when present, were small (see Supplementary Fig. 3 for the distribution of mean difference scores). Nonetheless, these effects were similar in size to the effect of mildly positive photos on happiness—that is, facial feedback was just as impactful as the external emotional context. Observing small effects is inconsistent with extreme claims that facial feedback is the primary determinant of emotional experience 2 , 74 . However, they support less extreme theories that characterize facial feedback as one of many components of the peripheral nervous system that contribute to emotional experience 47 , 75 , 76 .

These results have implications for discussions about whether facial feedback interventions—such as those that might ask people to simply smile in the mirror for five seconds every morning—can be leveraged to manage distress 15 , 16 , improve well-being 17 , 18 and reduce depression 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 . It is possible that relatively small facial feedback effects could accumulate into meaningful changes in well-being over time 77 . However, given that the similar-sized effect of positive images on happiness has not emerged as a serious well-being intervention, many (but not all) authors of this paper find it unlikely that facial feedback interventions will either.

Contrary to our predictions, the effect of posed facial expressions on happiness varied depending on the facial movement task. There was strong evidence of facial feedback effects in the facial mimicry and voluntary facial action tasks, but the evidence was less clear in the pen-in-mouth task. (This was despite avoiding video recording participants, which some 50 —but not all 59 —researchers argue interferes with facial feedback effects.) Our preregistered model with random slopes did not provide significant evidence of a simple effect of Pose in the pen-in-mouth condition, and Bayesian analyses provided moderate support for the null hypothesis. An exploratory one-sided test of this effect was significant when we removed random slopes from the model, but Bayesian analyses characterized the evidence as inconclusive. However, when we relaxed our inclusion criteria, both frequentist and Bayesian analyses provided strong evidence of a facial feedback effect in the pen-in-mouth task. Nonetheless, we preregistered that this would be considered a less stringent test of the facial feedback hypothesis.

Although it is less clear whether the pen-in-mouth task had a non-zero effect on feelings of happiness, the effect is clearly smaller than that produced by the facial mimicry and voluntary facial action tasks. This may suggest that different mechanisms underlie the effects produced by each task. Researchers do not agree on which mechanisms underlie facial feedback effects 73 , but they may involve both inferential processes (for example, people inferring they are happy because they are smiling) 45 , 46 and non-inferential processes (for example, smiling automatically activating other physiological components of emotion) 5 , 54 . Unlike other facial feedback tasks, the pen-in-mouth task was designed to limit the role of inferential process by manipulating facial expressions covertly 41 . Consistent with this goal, participants in the pen-in-mouth condition were less likely to report that the posed happy expression felt genuine. This may mean that inferential processes were minimized in this task, thus reducing the size of the facial feedback effect. Contrary to this explanation, though, we did not find that facial feedback effects were moderated by self-report measures of general attentiveness to non-emotional bodily process. (See the Supplementary Information for similar results from pilot studies using a multifaceted self-report of body awareness.)

Alternatively, the pen-in-mouth task may have created a less prototypical expression of happiness—which, regardless of the role of inferential processes, may attenuate facial feedback effects 51 , 52 , 53 . Specifically, facial feedback effects may be amplified when the task activates muscles typically associated with an emotional state and attenuated when the task activates muscles not typically associated with an emotional state. In retrospect, the pen-in-mouth task we used may simultaneously activate muscles associated with biting, which may attenuate its effect on happiness reports. Furthermore, a robust pen-in-mouth effect may emerge if one uses a variant of the task that better activates the orbicularis oculi muscles, which is associated with genuine expressions of happiness 56 . However, our results provide mixed support for these predictions. On one hand, facial feedback effects did not differ between the other two tasks, which were designed to produce less prototypical (voluntary facial action task) and more prototypical (facial mimicry task) expressions of happiness. On the other hand, facial feedback effects were larger when participants reported posing higher-quality expressions. Future research can further investigate this issue by more directly measuring muscle activity using facial action coding 78 , electromyography 79 , sonography 80 or thermography 81 .

To conclude, our adversarial collaboration was partly inspired by conflicting narratives about the validity of the facial feedback hypothesis. We began the collaboration after a large team of researchers failed to replicate a seminal demonstration of facial feedback effects using a pen-in-mouth task 40 , but a meta-analysis indicated that facial feedback has a small but significant effect on emotional experience 59 . Our results do not provide unequivocal evidence of a pen-in-mouth effect. Nonetheless, they do provide strong evidence that other tasks designed to produce partial or full recreations of happy expressions can both modulate and initiate feelings of happiness. It has been nearly 100 years since researchers began famously debating whether peripheral nervous system activity is merely a by-product of emotion processes. Consistent with theories positing that peripheral nervous system activity impacts emotional experience, our results a century later provide strong evidence of facial feedback effects. With this foundation strengthened, future researchers can turn their attention to answering new questions about when and why these effects occur.

Each research group received approval from their local Ethics Committee or Institutional Review Board to conduct the study (for example, University of Tennessee IRB-19-05313-XM), indicated that their institution does not require approval for the researchers to conduct this type of research or indicated that the current study is covered by a pre-existing approval. At the time of Stage 1 submission, 22 research groups had ethics approval to collect data, but additional sites with pending ethics approval joined the project later. All participants provided informed consent.

The experiment was presented via Qualtrics. Due to constraints created by COVID-19, we planned for data collection to primarily occur online. However, research groups were allowed to collect data in the laboratory if they indicated they could do so safely. Before beginning the study, the participants were asked to confirm that they had a clean pen or pencil nearby that they were willing to place in their mouths, were completing the study on a desktop computer or laptop (details regarding the participants’ operating systems were automatically recorded to confirm) and were in a setting with minimal distractions.

The participants were told that the study was investigating how physical movements and cognitive distractors influence mathematical speed and accuracy and that they would complete four simple movement tasks and math problems. The first and last tasks were randomly presented filler trials that helped ensure the cover story was believable (“Place your left hand behind your head and blink your eyes once per second for 5 seconds” and “Tap your left leg with your right-hand index finger once per second for 5 seconds”). In the two critical tasks, the participants were asked to pose happy and neutral facial expressions in randomized order through the facial mimicry, voluntary facial action or pen-in-mouth procedure. While posing these expressions, some participants were randomly assigned to view positive images. To reinforce the cover story, the participants were provided with an on-screen timer during all tasks.

After each task (including the filler tasks), the participants completed a simple filler arithmetic problem and the Discrete Emotions Questionnaire’s four-item happiness subscale, which asked the participants to indicate the degree to which they experienced happiness, satisfaction, liking and enjoyment during the preceding task (1 = ‘not at all’ to 7 = ‘an extreme amount’) 82 . The participants also completed two items measuring anxiety (worry and nervous). To further obscure the purpose of the study, the participants also completed one anger, tiredness and confusion filler item. All emotion items were presented in random order. By not referencing the emotional stimuli, this questionnaire better captured self-focused, as opposed to world-focused, emotional experience 57 , 58 . Afterwards, the participants rated how much they liked the task and how difficult they found the task and arithmetic problem. In the non-filler tasks, an attention check item asking the participants to choose a specific response option was randomly inserted in the questions regarding the task and arithmetic problem difficulty.

In the facial mimicry condition, the participants were shown a 2 × 2 image matrix of actors posing happy expressions. The participants were then instructed to either mimic these expressions (happy condition) or maintain a blank expression (neutral condition). Importantly, having the participants view the happy expression matrix before both the happy and neutral trials ensured that any potentially confounding effects that images of smiling people have on emotional experience were constant across the mimicry trials. The expression matrix was displayed for at least five seconds, and the participants indicated when they were ready to perform the task. In the voluntary facial action condition, the participants were instructed to either move the corners of their lips up towards their ears and elevate their cheeks using only the muscles in their face (happy condition) or maintain a blank facial posture (neutral condition). In the pen-in-mouth condition, the participants received video instructions regarding the correct way to hold the pen in their teeth (happy condition) or lips (neutral condition). During all facial pose tasks, the participants were instructed to maintain the poses for five seconds, the approximate duration of spontaneous happiness expressions 83 .

After completing the five movement tasks, the participants answered a variety of open-ended questions regarding their beliefs about the purpose of the experiment via Qualtrics. Each research group recruited two independent, results-blind coders to review the open-ended responses. The coders were provided a written description of the study purpose and methods and subsequently reviewed the participants’ open-ended responses in randomized order. On the basis of the open-ended responses, the coders rated the degree to which each participant was aware of the true purpose of the experiment (1 = ‘not at all aware’ to 7 = ‘completely aware’).

After answering questions about their beliefs regarding the purpose of the experiment, the participants completed a short demographic form and the Body Awareness Questionnaire 84 . The participants then answered several questions related to the quality of their data. First, the participants were re-presented with their assigned happy pose instructions and asked to retrospectively rate how well they followed the instructions earlier in the study (1 = ‘not at all’ to 7 = ‘exactly’). Second, the participants were asked to repeat the task and rate the degree to which it felt like they were expressing happiness (1 = ‘not at all’ to 7 = ‘exactly’). Third, the participants were asked to watch themselves repeat the task (for example, via a mirror or camera phone) and indicate the degree to which their expression matched an image of an individual completing the task correctly (1 = ‘not at all’ to 7 = ‘exactly’). Fourth, the participants were asked to describe any issues that may have compromised the quality of their data (such as distractions). The two coders from each research group reviewed the responses to this last question and rated the degree to which each participant was distracted (1 = ‘not at all distracted’ to 7 = ‘completely distracted’). The participants were told that there would not be a penalty for indicating that they did not complete the task correctly or that there were issues with the quality of their data.

Ideally, the quality of the participants’ posed expressions would have been assessed via video recordings or participant-submitted photos. However, many members of our collaboration expressed doubts about receiving ethical approval to collect and share images or recordings. Participants in many of our data collection regions may also have lacked a web camera. Furthermore, researchers are still debating whether awareness of overt video recording interferes with facial feedback effects 49 , 50 , 59 , 85 . Nevertheless, pilot study recordings and self-reports confirmed that almost all participants successfully posed the target facial expressions ( Supplementary Information ).

In the facial mimicry task, the participants all viewed the same 2 × 2 image matrix of actors posing happy facial expressions from the Extended Cohn–Kanade Dataset 86 . All four actors posed prototypical facial expressions of happiness, as confirmed by coders trained in the Facial Action Coding System 78 . An image matrix of actors, as opposed to a single image, was used so that the participants had multiple examples of the movement and were provided with more options for a suitable facial model. In the pen-in-mouth task, the instructional videos were adopted from Wagenmakers and colleagues’ replication materials 40 .

During the two facial expression pose tasks, one group of participants viewed an array of four positive photos (for example, photos of dogs, flowers, kittens and rainbows). Multiple photos (as opposed to a single photo) were used to increase the probability that the participants found at least one of the photos emotionally evocative. All photos were drawn from a database comprising 100 images from the internet and the International Affective Picture System 87 that were separately rated on how good and bad they were 88 . The results from the three pilot studies confirmed that these images successfully elicited feelings of happiness ( Supplementary Information ). Due to potential cross-cultural differences in what types of photos elicit happiness (for example, dog photos can be expected to elicit happiness in many Western cultures but not in all African cultures), each lab was permitted to replace photos with more culturally appropriate positive photos. For non-English-speaking data collection sites, the experiment materials were translated into the local language.

Due to the nested nature of the data (for example, ratings nested within individuals, which were nested within research groups), we used linear multilevel modelling. More specifically, happiness reports were modelled with (1) Pose, Facial Movement Task and Stimuli Presence entered as factors; (2) random intercepts for research groups and participants; and (3) random slopes for research groups. All hypotheses in Table 1 were examined using both null hypothesis significance testing and Bayesian alternatives.

Participants were excluded from the primary analyses if they (1) exhibited any awareness of the facial feedback hypothesis (that is, received an awareness score over 1 from two independent coders), (2) disclosed that they were very distracted during the study (that is, received an average distraction score above 5 from two independent coders), (3) did not complete the study on a desktop computer or laptop, (4) indicated that they did not follow the pose instructions, (5) indicated that their expression during the happy pose task did not at all match the image of an actor completing the task correctly, or (6) failed attention checks. These stringent exclusion criteria were added after we failed to observe the pen-in-mouth effect in pilot study 3.

Although our primary analyses were run with the aforementioned exclusion criteria, we also re-ran these analyses to examine whether the exclusion criteria interact with Pose to influence happiness reports. We also examined whether these exclusion criterion variables varied as a function of Facial Movement Task and Stimuli Presence.

To examine the alternative explanation that doing something (for example, posing a happy facial expression) may simply be more enjoyable than doing nothing (for example, posing a neutral facial expression), we also re-ran our primary analyses with a factor contrasting the happy pose and filler trials.

Although previous research has indicated that many psychology studies yield similar effect sizes when completed online versus in a lab 89 , we recorded the mode of data collection and planned to re-run our primary analyses with the data collection mode included as a moderator. However, we noted that this analysis may be confounded by (1) whether the research group is a proponent or a critic of the facial feedback hypothesis (that is, proponents may be more likely to collect data in the laboratory) and (2) the region of data collection (that is, research groups in regions with fewer COVID-19 cases may be more likely to collect data in the laboratory).

Although we did not anticipate a Pose by Facial Movement Task interaction, we noted that the pen-in-mouth condition may lead to heightened levels of anxiety in the midst and/or aftermath of COVID-19. Although this is speculative, heightened levels of anxiety may interfere with facial feedback effects. Consequently, as an exploratory analysis, we examined whether anxiety ratings differ as a function of Facial Movement Task.

Power simulation

Power analysis was performed via a linear multilevel modelling simulation. We randomly generated normally distributed data for 96 participants from 22 research groups. Effect size estimates for the hypothesized effects of Pose ( d  = 0.39), Stimuli Presence ( d  = 0.68) and the Pose by Stimuli Presence interaction ( d  = 0.29) were estimated from pilot studies 1 and 2 ( Supplementary Information ). All other effects were set to zero. Pilot study 3 was run after initial in-principle acceptance was granted and yielded somewhat different effect size estimates. However, this pilot study led to minor refinements in the exclusion criteria that left our original predictions unchanged.

On the basis of two pilot studies, we simulated random intercepts for participants with s.d. = 0.70. We did not simulate random slopes for participants since there are only two observations within each participant, which would probably lead to convergence issues. Random slopes for research groups were simulated on the basis of the values from the previous many-lab failure to replicate 40 . For the hypothesized effects, we specified conservative random slope estimates on the basis of the standard deviation of their meta-analytic effect size from the previous many-lab failure to replicate (s.d. = 0.28). For the effects we expected to be zero, we specified random slopes on the basis of the random slope from the previous many-lab failure to replicate ( τ 2  ≈ 0). However, due to convergence issues, the research groups random slope for the facial feedback task factor was removed. Residual variance was set to 0.60 on the basis of the estimates from pilot studies 1 and 2.

The results from this power simulation indicated that over 95% power for all our hypothesized effects could be obtained with at least 1,584 participants. However, on the basis of pilot study 3, we estimated that 44% of the participants would not meet our strict inclusion criteria, leading to a desired sample of 2,281. We therefore planned to stop collecting data once one of the following conditions was met: (1) 22 labs had collected 105 participants each or (2) at least six months had elapsed since the start of data collection and we had at least 2,281 participants. We planned for a minimum of 22 labs to collect data for this project, although additional labs with pending ethics approval were allowed to join the project later.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The full data are publicly available at https://osf.io/ac3t2/ . Source data are provided with this paper.

Code availability

The full analysis code is publicly available at https://osf.io/ac3t2/ .

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Acknowledgements

This work was financially supported by B. Stastny, who generously donated funds for this research in memory of his father, Bill Stastny (J.T.L.). The work was also supported by the National Science Centre, Poland (grant no. 2019/35/B/HS6/00528; K.B.), JSPS KAKENHI (grant nos 16H03079, 17H00875, 18K12015, 20H04581 and 21H03784; Y.Y.), the National Council for Scientific and Technological Development (CNPq; R.M.K.F.), the Polish National Science Center (M.P.), the DFG Beethoven grant no. 2016/23/G/HS6/01775 (M.P.), the National Science Foundation Graduate Research Fellowship (grant no. R010138018; N.A.C.), the Ministerio de Ciencia, Innovación y Universidades (grant no. PGC2018-098558-B-I00; J.A.H.), the Comunidad de Madrid (grant no. H2019/HUM-5705; J.A.H.), Teesside University (N.B.) and the Occidental College Academic Student Project Award (S.L.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We also thank C. Scavo and A. Bidani for help with translating the study materials, L. Pullano and R. Giorgini for help with coding, and E. Tolomeo and L. Pane for help with data collection.

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Conceptualization: N.A.C., D.S.M., F.M.-R., J.T.L., J.F.H., P.M.G., P.C.E., L.G. and F.S. Data curation: N.A.C., B.S., Y.Y. and S.R.-F. Formal analysis: N.A.C., L.G., M.M. and M.T.L. Funding acquisition: N.A.C., Y.Y. and N.B. Investigation: N.A.C., D.S.M., J.T.L., N.C.A., I.L.G.N., M.L.W., F.F., N.R., A.M., J.F.H., G.K., E.Y., A.K., N.H., J.T., R.M.K.F., D.Z., B.A., K.B., S.A., K.F., Y.Y., A.I., D.L.E., C.A.L., S.L., M.P., N.B., G.P., D.M.B.-B., J.A.H., P.R.M., L.G.J.D., K.V., H.IJ., N.T., S.D.P., P.M.G., A.A.Ö., S.R.-F. and M.T.L. Methodology: N.A.C., D.S.M., F.M.-R., P.S.F., J.F.H., G.K., K.B., D.L.E., S.R.-F., P.C.E. and L.G. Project administration: N.A.C., M.L.W., F.F., P.S.F., J.F.H., J.T., K.B., K.F., D.L.E., M.P., H.IJ., S.D.P. and A.A.Ö. Resources: N.A.C., D.S.M., I.L.G.N., E.Y., A.K., T.N., R.M.K.F., B.A., K.B., S.A., M.P., G.P., J.A.H., P.R.M., H.IJ., P.M.G., A.A.Ö. and S.R.-F. Software: N.A.C., J.T. and M.M. Supervision: N.A.C., N.C.A., F.F., N.R., J.F.H., B.A., K.B., C.A.L., N.B., H.IJ. and S.D.P. Validation: N.A.C., P.S.F., N.H., J.T., M.P., N.T., M.M. and M.T.L. Visualization: N.A.C., P.S.F., J.A.H. and L.G. Writing—original draft: N.A.C., D.S.M., A.A.Ö. and L.G. Writing—review and editing: N.A.C., D.S.M., F.M.-R., J.T.L., N.C.A., I.L.G.N., M.L.W., F.F., N.R., A.M., P.S.F., J.F.H., G.K., T.N., N.H., D.Z., B.A., K.B., Y.Y., D.L.E., N.B., G.P., D.M.B.-B., J.A.H., P.R.M., L.G.J.D., H.IJ., N.T., S.D.P., P.M.G., A.A.Ö., S.R.-F., P.C.E., L.G., F.S., M.M. and M.T.L.

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Data on country-specific sample sizes.

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Participant-level data for the primary analyses.

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Participant-level data for the secondary moderator analyses.

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Coles, N.A., March, D.S., Marmolejo-Ramos, F. et al. A multi-lab test of the facial feedback hypothesis by the Many Smiles Collaboration. Nat Hum Behav 6 , 1731–1742 (2022). https://doi.org/10.1038/s41562-022-01458-9

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Facial feedback hypotheses: Evidence, implications, and directions

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  • Volume 20 , pages 121–147, ( 1996 )

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This review evaluates four facial feedback hypotheses, each proposing a certain relation between the face and emotions. It addresses criticisms of the data, considers implications for emotional and social processes, and advises directions for future research. The current data support the following: Facial actions are sensitive to social context, yet correspond to the affective dimension of emotions; matches with specific emotions are unlikely. They modulate ongoing emotions, and initiate them. These two claims have received substantially improved support, in part due to studies controlling for effects of experimental demand and task difficulty. Facial action may influence the occurrence of specific emotions, not simply their valence and intensity. Facial action is not necessary for emotions. There are multiple and nonmutually exclusive plausible mechanisms for facial effects on emotions. Future work must focus on determining the relative contributions of these mechanisms, and the parameters of their effects on emotions.

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Daniel N. McIntosh

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I appreciate the helpful comments of Harry Gollob, Greg McHugo, Catherine Reed, Craig Smith, and R. B. Zajonc on earlier drafts of this paper.

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McIntosh, D.N. Facial feedback hypotheses: Evidence, implications, and directions. Motiv Emot 20 , 121–147 (1996). https://doi.org/10.1007/BF02253868

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Issue Date : June 1996

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How Does Facial Feedback Modulate Emotional Experience?

Joshua ian davis.

Barnard College of Columbia University

Ann Senghas

Kevin n. ochsner.

Columbia University

Contracting muscles involved in facial expressions (e.g. smiling or frowning) can make emotions more intense, even when unaware one is modifying expression (e.g. Strack, Martin, & Stepper, 1988 ). However, it is unresolved whether and how inhibiting facial expressions might weaken emotional experience. In the present study, 142 participants watched positive and negative video clips while either inhibiting their facial expressions or not. When hypothesis awareness and effects of distraction were experimentally controlled, inhibiting facial expressions weakened some emotional experiences. These findings provide new insight into ways that inhibition of facial expression can affect emotional experience: the link is not dependent on experimental demand, lay theories about connections between expression and experience, or the distraction involved in inhibiting one’s expressions.

After a stressful day, have you ever become aware of just how tightly you were clenching your jaw, furrowing your brow, or squinting your eyes? Such facial expressions can show the world what we are feeling inside. They are, after all, the result of our emotional states. But is it possible that the reverse is also true – that our emotional states are the result of our facial expressions?

Historically, there has been great interest in this question ( Darwin, 1872 ; Izard, 1971 ; Laird, 1984 ; Niedenthal, 2007 ; Tomkins, 1962 ). One of the first arguments that expressions influence emotional experience came from William James and Carl Lange. For James and Lange, the direct perception of a particular somatic state (visceral, postural, or facial), was the essence of what it meant to have a particular emotional experience (for review see Fehr & Stern, 1970 ; James, 1884 , 1890 , 1894 ; Lange, 1885/1912 ). Although the James-Lange theory pertained to expressions throughout the body in addition to facial expressions, their theory anticipated later work on the Facial Feedback Hypothesis (FFH) ( Ekman, Levenson, & Friesen, 1983 ; Izard, 1971 ; Tomkins, 1962 , 1963 ; Tourangeau & Ellsworth, 1979 ) that focused on facial expressions alone and their influence on emotional experience.

Different versions of the FFH make different claims about the relative importance of facial feedback in emotional experience. According to the necessity hypothesis , without facial feedback there can be no emotional experience ( Keillor, Barrett, Crucian, Kortenkamp, & Heilman, 2002 ). Keillor et. al. studied a woman with total facial paralysis, who nevertheless demonstrated typical emotional responses to emotionally evocative photographs, effectively ruling out this hypothesis. According to the sufficiency hypothesis (e.g. Ekman et al., 1983 ), facial expressive muscle activity on its own can produce emotional experience. There has been support for this hypothesis; for example, directing people to contract muscles that are associated with facial expressions of emotion can be sufficient to elicit the associated emotions ( Levenson & Ekman, 2002 ). Finally, the modulation hypothesis (e.g. Strack, Martin, & Stepper, 1988 ) holds that facial expression can modulate emotional experiences that have been elicited by some external stimulus, something other than one’s own facial actions. It is this modulation hypothesis that is tested in the present study. In particular, we seek to address gaps in existing research that have left this hypothesis unresolved.

There have been two main approaches to examining how changes to facial expression can modulate emotional responses. The most well-studied approach asks participants to generate facial expressions, and records any resulting changes in self-reported emotional experience. This research is perhaps best exemplified by the now classic study by Strack, Martin, and Stepper (1988) , which found that asking participants to generate smile-related expressions led them to report enhanced positive affect, whereas having them inhibit smile-related expressions by activating opposing muscles weakened positive affect. Strack et al.’s methods have since been replicated by other researchers, with similar results (e.g. Soussignan, 2002 ). Other research on how generating facial expressions can modulate emotional experience that is in response to stimuli tends to support these findings (for reviews see Adelman and Zajonc, 1989 , Capella, 1993 , Laird 1984 , Matsumoto, 1987 , McIntosh, 1996 , and Soussignan, 2004 ). In general, smiling makes a person feel more positive, and frowning makes a person feel more negative.

A second approach examines the effects of inhibiting facial expression on emotional experience. This approach has been employed by only a handful of studies, in which participants view emotional stimuli and, rather than being asked to generate an expression, are instructed to keep a constant neutral expression on the face, and to not allow emotional expressions to appear. Although the FFH would predict that inhibiting facial expression should decrease the strength of emotional experience, results have been mixed. Studies have variously shown: a) a decrease in negative emotional experience when participants inhibited facial and bodily expressions ( Duclos & Laird, 2001 ), b) a decrease in positive emotional experience when participants inhibited facial expression ( Bush, Barr, McHugo, & Lanzetta, 1989 ), and, with inhibition of micro-expressive changes in facial expression, c) both a decrease in positive and a marginal decrease in negative emotional experience ( McCanne & Anderson, 1987 ). Finally, although Strack et al. did not guide participants to hold a neutral expression, they did find lower positive affect when participants inhibited smile-related activity by activating opposing muscles ( Strack et al., 1988 ).

The emotional effects of inhibiting facial expression also have been examined in experiments in which participants are instructed to suppress the expression of their emotions as a form of emotion regulation ( Gross, 1998a ). Although suppression studies direct participants to hide all behavioral expressions of emotion, and not just those on their faces, for present purposes they are informative because the face is likely the dominant channel of emotional expression ( Darwin, 1872 ; Tomkins, 1962 , 1963 ), especially in laboratory experiments. This implies that the expressions that are most inhibited in a suppression study are those that are on the face. To date, studies of suppression have focused primarily on inhibiting expressive responses to negative emotions, again with mixed results. Studies have variously shown: a) a decrease in the strength of various negative emotions for older, but not middle-aged and younger adults ( Magai, Consedine, Krivoshekova, Kudadjie-Gyamfi, & McPherson, 2006 ), b) no effect on negative emotion ( Gross, 1998b ), c) a significant drop in negative emotion ( Goldin, McRae, Ramel, & Gross, 2008 ), and, in two of only three studies that we are aware of to look at both positive and negative emotion, d) a decrease in positive but not negative emotional experience in one instance ( Gross & Levenson, 1997 ), and no reported differences as compared to spontaneous expression in the other ( Zuckerman, Klorman, Larrance, & Spiegel, 1981 ).

Taken together, this previous work is at least partly consistent with the idea that the inhibition of facial expression decreases the magnitude of emotional experience in response to emotional stimuli. However, at least four important questions remain about the effects of facial expression inhibition on experience that limit the strength of the conclusions that can be drawn from prior work.

First, there is the question of whether inhibition affects positive and negative emotions equally. To date, few studies have considered both positive and negative emotions in the same study. This leaves a critical gap in the logic of the argument, because considering positive or negative emotion alone cannot dissociate an increase or decrease in the strength of emotional experience from a general shift towards feeling more positive or more negative. For example, posing a frown might make one feel more negative, or it might simply disrupt or weaken any emotional experience, positive or negative. Although a few studies have included both positive and negative stimuli ( Gross & Levenson, 1997 ; McCanne & Anderson, 1987 ; Zuckerman et al., 1981 ), they have not addressed each of the additional considerations listed below.

Second, there is the question of whether the documented effects of inhibition are indirectly the consequence of the distraction of devoting resources towards inhibiting facial expressions while also attempting to watch video clips or fill in questionnaires related to emotion. Extant experiments on inhibition report changes in emotional experience in terms of overall decreases in emotional experience, which could also be caused by distraction. Indeed, in research on the relative value of different emotion regulation strategies, participants asked to think distracting thoughts rather than ruminate on their depression or anger experienced less negative emotion as a result (e.g. Nolen-Hoeksema & Morrow, 1993 ; Rusting & Nolen-Hoeksema, 1998 ). Two studies have addressed the question of how distraction might compare to inhibiting facial expression in response to emotional stimuli ( Duclos & Laird, 2001 ; Richards & Gross, 2006 ). Richards and Gross (2006) explicitly instructed participants to either distract themselves with “thoughts that have nothing to do with [an emotional video clip]” or to inhibit (specifically to suppress) their emotional expressions while watching video clips. They found that distraction reduced self-reported emotional experience, whereas expressive suppression did not ( Richards & Gross, 2006 ). These data suggest that distraction and inhibition of expression are not identical. Duclos and Laird induced negative affect by having participants in two groups recall sad or angry life experiences. Each group was then asked to perform one of the following tasks: either to sort a deck of cards by suit and order (distraction), or inhibit their emotional expressions. Each group then switched to the other emotion and then performed the task they had not yet performed (distraction or inhibition). The authors found that both distraction and inhibition of expression decreased the strength of negative affect ( Duclos & Laird, 2001 ). Although the reasons for these discrepant results are not immediately apparent, our point here is that these studies included only negative stimuli, and asked participants to inhibit not only their facial expressions but all behavioral manifestations of emotion. Thus, the relative effects of facial inhibition, per se, as opposed to distraction, on both positive and negative responses have not yet been examined. Furthermore, the type of attentional control required for facial inhibition is akin to that in a divided attention study in which participants must attend to perceptual stimuli while simultaneously attending to and controlling their facial expressions. This may be importantly different from simply shifting one’s attention away from a stimulus, as was done in prior research.

The third question concerns participants’ awareness of the experimental hypothesis. In the Strack et al. studies of posing facial expressions, as well as subsequent studies employing variants of those methods, a carefully constructed cover story was used to ensure that participants were not aware that the study pertained to facial expression or emotion. It was thus possible to attribute changes in emotional experience to facial feedback, and not to experimental demand or other effects on self-reports that might follow from participants’ holding conscious expectations about how expression and experience should connect. Studies of facial inhibition have not emphasized cover stories to the same degree, however (e.g. Bush et al., 1989 ; Duclos & Laird, 2001 ; McCanne & Anderson, 1987 ). Furthermore, related studies of expressive suppression have explicitly instructed participants to “hide their emotions” so that others could not tell what the participant is feeling, an instruction that could engender expectancies in participants regarding how much their self-reported emotional experience should be independent of their facial expression. Thus, it is not yet clear whether the effects of facial inhibition on experience should be attributable to the lack of feedback per se .

A fourth and final question is whether participants who are instructed to inhibit their facial expressions engage in cognitive strategies – such as reappraisal of the stimulus as something less affectively potent – to make it easier to hold their faces still. While a handful of researchers have data that speak to this possibility (e.g. Goldin et al., 2008 ) it has not been addressed in the majority of work on the topic. The use of such strategies would be problematic, because any observed changes in experience could be attributable to the strategies rather than to changes in facial feedback.

Overview of the present study

The aims of this study were to examine the effects of inhibiting facial expression while (a) investigating both positive and negative emotion, (b) ensuring that participants were not aware of the study’s interest in the connection between facial expression and emotional experience, (c) beginning to explore whether alternative cognitive strategies might be at play, and (d) providing a new control for the effects of distraction.

As a cover story, participants were told that we were monitoring brain-wave activity associated with memory and attention. They wore electrodes on their faces for this monitoring, and participants in the critical no movement group were told that they must not move at the location of the electrodes because movement would compromise the brain-wave data. We also buried the emotion-related questions within a majority of non-emotional filler questions, included as many neutral video clips as overtly emotional ones, and hid the video camera from view. Finally, we conducted a debriefing interview to determine to what degree participants had inferred that the study pertained to a connection between facial expression and emotional experience. At the end of this interview we also asked participants about the strategies they might have used to comply with the instructions they were given in the no movement condition, as some strategies may have relied on recognizing an expression-experience link. We predicted that even under these highly conservative circumstances, inhibiting facial expression (by not moving at the locations of the electrodes) would decrease the strength of emotional experience.

We also attempted to address the potential distraction involved in facial inhibition tasks. We required participants in our distraction condition to count backwards by threes while watching the video clip stimuli. This task was chosen because the distracting effects of arithmetic tasks such as counting backwards are well characterized in dual-task distraction research (e.g. Allen, Baddeley, & Hitch, 2006 ; Castel, Pratt, & Craik, 2003 ), and can be performed without directly interfering with the perception of the video or audio portions of the video clips.

Participants

Participants were 142 members of the Columbia University community, 90 female and 52 male, between the ages of 18 and 57 (M=22.2 yrs, SD =5.3 yrs). Participants were paid at a rate of $10/hour, or received class credit in an Introductory Psychology course. Participants were randomly assigned to one of four groups: (a) No instructions (control), (b) no movement , (c) distraction , and (d) no instructions & no electrodes . The groups were defined by the different instructions they were given following the cover story. The data from eight participants were not usable due to equipment malfunction, leaving 35 (M=23.5 yrs, SD=7.3 yrs, 19 female, 16 male) in the no instructions group, 34 (M=21.0 yrs, SD=3.6 yrs, 23 female, 11 male) in the no movement group, 33 (M=21.8 yrs, SD=4.1 yrs, 25 female, 8 male) in the distraction group, and 32 (M=22.3 yrs, SD=5.1 yrs, 18 female, 14 male) in the no instructions & no electrodes group.

The stimuli were four video clips, each between 2 and 3 minutes in length (M=2.3 mins), one positive, one negative, and two neutral. The positive video clip was a collection from the television program “America’s Funniest Home Videos,” depicting physical humor, such as a fluffy dog being pushed around like a mop. The negative video clip was composed of footage from the television show “Fear Factor,” depicting a man eating a live-worm sausage. One neutral video clip contained segments from a documentary on Jackson Pollock, and a second neutral video clip was a selection from a documentary entitled “The Way Things Go,” depicting a Rube Goldberg-like chain reaction. Informal pre-testing suggested that it was difficult to select a truly neutral video clip that elicited no emotional responses whatsoever. Seeking comparatively neutral video clips so that participants would not solely be responding to strongly emotional stimuli, we selected mildly positive clips to use in our ‘neutral’ conditions. The neutral clips were included as one means of suggesting to participants that the study did not pertain directly or entirely to emotional experience. The inclusion of these clips also provided additional film clips for which the primary hypotheses could be tested. The video clips were presented on a screen area of approximately 4.5″×6″. Viewing distance was 18 to 24 inches.

Group instructions

All participants in the no instructions , no movement , and distraction groups were told that we would be monitoring brain-wave activity related to memory and attention. They were informed that an experimenter would be placing recording electrodes on various locations on their heads in order to monitor brain-wave activity. The experimenter indicated the locations on his or her own face, pointing to the forehead, the area between and just above the eyebrows, the area around the outside of the eyes, and the cheeks. Because participants in the no instructions & no electrodes group did not wear electrodes, they were not told that we were monitoring brain-wave activity, but were informed that we were interested in memory and attention. All participants were informed that they were part of a control group in a research study about the effects of general anesthesia on memory and attention. The notion that they were in a control group was meant to further limit the degree to which they were likely to search for ways in which the experimental procedures might be affecting their responses. Participants were then instructed in the procedures for watching the video clips and answering questions on the computer.

Participants in the no movement and distraction groups then received additional instructions. Participants in the no movement group were told that movement of the muscles under the recording disks could interfere with the brain-wave signal and render the data useless. For this reason, they were told they must keep from moving the muscles near the recording disks during the video clips, as that is the time during which we were most concerned about brain-wave activity pertaining to attention and encoding of memories. They could move as they liked between clips.

Participants in the distraction group were told that they would be asked to count backwards by threes throughout the duration of each video clip. They would be given a random number between 500 and 1000 at the start of each video clip, and asked to count, for example, down to 997, 994, and so on, and to finally provide the number to which they arrived at the end of the video clip. To guide participants to continue performing the distracting task, participants were instructed to start over from the original given number should they lose track of what number they had counted to.

Following these instructions, participants were seated in front of the stimulus presentation computer, and the facial electrodes (depending on condition) were attached. Finally, they were instructed that we had a large number of stimuli and that the computer randomly picked four or five from among them depending on the time allotted for each participant’s session. This was meant to further limit the degree to which participants might search for themes, such as emotional relevance, among the video clips.

Electrode placement

Using a method similar to that used by Bush et al. (1989) , dummy electrodes were placed on the faces of all participants (excepting those in the no instructions & no electrodes group), and participants were told that these were the electrodes through which we were monitoring brain-wave activity. For the purposes of this study, it was important that the locations of the electrodes be over key muscle groups whose activity has been correlated with emotional experience ( Cacioppo, Berntson, Larsen, Poehlmann, & Ito, 2000 ; Ekman, Friesen, & Ancoli, 2001 ). These muscle groups included the zygomatic muscles (smiling), the orbicularis oculi (laugh lines), the corrugator supercilii (frowning, furrowing the brow), and the frontalis (raising the brow). Locating the appropriate placement for the electrodes was done according to Fridlund and Cacioppo (1986) .

Following dummy facial electrode placement, participants were reminded of the cover story and the specific instructions for their group, as well as of the instructions for use of the computer. Participants in the no movement group were also “shown” the effects of moving one of the wires attached to the electrodes on a recording of what participants had been led to believe was brain-wave activity, to convince them that the brain-wave signal could be easily overwhelmed with movement.

Stimulus presentation order

A neutral video clip always came first, in order to: (a) allow participants to become familiar with the types of questions they would answer and their format; (b) allow participants to become accustomed to having electrodes on their face; and (c) give a first impression that the study was not about emotion. For these reasons the data for this first neutral video clip, which was the same video clip for all participants (“The Way Things Go”), were not analyzed. However, participants were led to believe that this first video clip was no different from the others.

Self-report measures

After each video clip, participants completed a series of self-report measures, a majority of which were non-emotional filler questions, and one of which was to provide ratings of emotional experience as a result of the video on the dimension of valence (how positive or negative a person felt). They responded on a nine point Likert scale from −4 to 4, anchored with “Very negative” at −4, “Neutral” at 0, and “Very positive” at 4.

Following the self-ratings, participants were asked to speak aloud into a microphone for approximately one minute and to relate as much as they could remember. They were told that this free-recall question was one of our primary memory questions.

Distracter tasks

Following the self-report and spoken responses, participants completed word and math puzzles intended to reduce emotional carryover from one stimulus to the next. These included simple to moderate difficulty arithmetic problems and fill-in-the-blank word puzzles. These tasks had the further effect, as we later confirmed from our participants, of helping to lead many of them to believe that the study pertained to something other than emotion.

After completing the distracter tasks following the first video clip, participants then watched the next video clip, completed the self-report questions, the spoken memory question, and the distracter tasks, repeating the process for each of the three remaining video clips (one negative, one neutral, and one positive), whose order was counterbalanced within and between groups. Timing was self-paced at each stage. Participants were reminded of their specific group instructions prior to beginning each video clip. (See Figure 1 for an illustration of the methods).

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Graphical depiction of methods.

Debriefing interview

Following the distracter tasks after the final (fourth) video clip, participants completed a series of questions regarding their beliefs about the study that were modeled after the “funnel” debriefing interviews conducted by Bargh and colleagues ( Bargh, Chen, & Burrows, 1996 ). Participants were not explicitly given the hypothesis during this period; they were only asked about what they already believed. For this debriefing interview, the computer prompted participants to answer seven successive questions that progressively hinted at the hypothesis and encouraged participants to figure it out. Questions began as open-ended regarding the experiment, and later encouraged participants to find themes, to report on what they believed the study was about, and to search for potential alternative hypotheses besides what had been explained by the experimenters. Participants were scored according to the question at which two independent judges, who were blind to experimental condition, determined that the participant guessed that the study pertained to facial expression and/or to emotional experience. So as to have a conservative bias when scoring responses for hypothesis awareness, participants did not need to reveal that they had understood that the study pertained to the connection between facial expression and emotional experience, but simply that they suspected that the study’s goals might pertain to each topic in some way.

Three participants were identified, by at least one of the two judges, as having guessed that the hypotheses pertained in some way to both facial expression and emotional experience. Those three participants were excluded from all subsequent analyses. Debriefing interview data were not available for one participant, who was treated neither as having guessed the hypothesis, nor as having never guessed it. That participant’s data, however, were later excluded due to failure to comply with instructions as determined by the manipulation check (described below). Inter-rater reliability coefficients between the two judges were r = .576 regarding “at what question participants guessed that the hypothesis pertained to emotion,” and r = .661 regarding “at what question they guessed that the hypothesis pertained to facial expression.” One judge reported that 37 percent did not ever guess (a score of eight) that the study pertained to emotion even when asked to search for alternative purposes for the study besides memory and attention, and 85 percent never guessed it pertained to facial expression. The second judge reported 36 percent and 91 percent, respectively.

Strategies used

Participants in the no movement condition were asked at the completion of the debriefing interview to offer percentages representing the degree to which they felt that they used each of several strategies to keep the face from moving. The strategies that were probed were derived from the common themes that emerged in free reports during pilot testing. These included physical restriction (I just kept my muscles from moving), reappraisal (I changed the impact of what I was watching by reframing it as something else; for example, I reminded myself that this is only television and television can be fake), and distraction (I thought about something else so that I wouldn’t be thinking about what I was watching). Participants could also specify strategies not listed.

In order to be able to treat all four groups equally during the video clip watching and debriefing phases of the study, additional questions that pertained only to specific groups were held until after the interviews. Participants who had been given a second task ( no movement and distraction participants) were asked at this point to rate how distracting their task was. Ratings were made for each video clip individually. Participants were prompted to respond regarding the first video clip they saw, then the second, and so on. Distraction ratings were not completed by four participants (two from the no movement and two from the distraction groups).

Video Coding

Because a visible camera might have caused participants to become self-conscious of their facial expressions, and how they were coming across to an observer, the camera was hidden from view. Of course, all participants consented at the outset of the study to be videotaped, and likely expected to be videotaped at some point during the study. However, they were not told that the videotaping would take place specifically while they were watching the video clips.

We coded amount of expression. A trained judge, blind to the experimental hypothesis and to participant condition, coded the videos. The judge made ratings of expression with sliding knobs that sent continuous output in the form of a changing voltage signal, with end points representing a range from no expression to a lot of expression . The continuously changing voltage values were recorded on a BIOPAC Systems MP150 module. The integral of the area under the curve produced by this continuous recording provided a measure, in units of Volts × Seconds, of the amount of overall expression shown during the video clip. All ratings were made with the sound off so as to ensure that the soundtrack of the video clip could not be used to determine whether the participants were watching a negative, neutral, or positive video clip. The judge instructions were to code only what was visible on the screen, and not to attempt to infer what the participant was feeling. Rather than instruct the judge to search for particular muscle movements, we asked that he code any visible expressions that could be considered a positive or negative expression. Our measure was thus a sum of amounts of positive and negative expression. Prior to beginning, he was coached regarding how to use the equipment by allowing him to practice with a full range of photographs that had been edited to form a continuum from neutral to either strongly negative expressions or strongly positive expressions. 1

To provide inter-rater reliability, a second judge coded 30% of the video clips. We computed z-scores for each judge to account for differential use of the scales. Inter-rater reliability for amount of expression was then calculated two ways. Pearson’s r =.805, and the intraclass correlation was .782 ( King, 2004 ).

Eight of our video recordings were not usable for coding, due either to equipment failure or participants’ inadvertently blocking a clear view of their faces by turning their heads, or leaning their faces in their hands. One of those eight, a participant in the no movement group, did have usable video for both the positive and negative video clips, but not the neutral video clip; that participant’s videos could be evaluated using the manipulation check described below.

Manipulation Check

Participants in the no movement condition who showed facial expressions that were indistinguishable from an average member of the no instructions group were considered to have not followed instructions to refrain from moving. The 95 percent confidence interval for the no instructions group was used as the criterion for whether a participant in the no movement group was indistinguishable from those in the no instructions group. Because the manipulation involved refraining from any movement, we compared participants on our measure of overall amount of expression. Eight participants were found not to have followed instructions by these criteria and their data were excluded from all subsequent analyses. Of these eight, three were excluded due to expressing excessively in response to the negative video clip, two in response to the positive video clip, and three in response to both the negative and the positive video clips. Conservatively (that is, potentially increasing the noise in the data), the two participants in the no movement group whose video was unusable for the manipulation check were treated as though they had followed instructions, and included in all analyses.

Self-Report

In order to compare valence scores for all three video clips on a single metric, the scores for the negative video clip were multiplied by negative one. This made the group means positive for all video clips, and created a scale representing strength of emotional experience, whether positive or negative, with higher values indicating stronger emotional experience. A 4 (Group) × 3 (Video clip) mixed design omnibus analysis of variance (ANOVA) revealed a significant main effect of Video clip, F (2,238) = 13.981, p <.001, partial η 2 =.105.

A linear contrast of the no movement group vs. the other three groups combined yielded a significant main effect in which the no movement group reported weaker emotions than the other groups, F (1,119)=4.704, p =.032, d =.501. This contrast was significant at both the negative, F (1,119)=18.801, p <.001, d =1.003, and neutral video clips, F (1,119)=6.122, p =.015, d =.572, but was not significant at the positive video clip.

Our principle hypothesis concerned the comparison of the no movement group with the no instructions group. In that contrast, the no movement group reported significantly weaker emotional experience than did the no instructions group, F (1,119)=5.979, p =.016, d =.657 (see Figure 2 and Table 1 ). Additional planned contrasts at each level of video clip compared affect ratings for the no movement and no instructions groups. These analyses revealed significantly weaker emotional experience for the no movement group for the negative video clip, F (1,56)=4.330, p =.040, d =.559, and marginally significantly weaker emotional experience for the no movement group for the neutral video clip, F (1,56)=3.701, p =.057, d =.516, along with a non-significant trend in the same direction for the positive video clip. Note that when including the eight participants who did not follow instructions, the difference between the no movement and no instructions groups was still significant, p =.050. Also note that when the two participants from the no movement group who had no video that could be evaluated in the manipulation check were removed from the analysis, this effect of Group was still significant, p =.026. Similarly, when all participants from all groups who were missing video data were removed from the analysis, this effect was again still significant, p =.027.

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Average self-reported strength of emotional experience. Valence scores (how positive or negative a person felt) for the negative video clip were multiplied by −1 in order to place all video clips on the same scale, and therefore be able to test for the hypothesized main effect of an overall reduction in the strength of emotional experience.

Means and (SE) for Dependent Measures

Note. Self-Report measures are derived from 9 point Likert Scales (Valence ranging from −4 to 4, Distraction from 0 to 8). Valence scores for the negative video clip are multiplied by minus 1 so as to put them on the same scale as valence scores for the other video clips and create a measure of the strength of the emotional experience. Expression units are volts × seconds.

The no movement group did not significantly differ from the distraction group or the no movement & no electrodes group. Contrasts at each level of video clip, revealed that the no movement group reported marginally weaker emotion in response to the negative video clip than did the distraction group, F (1,54)=3.465, p =.065, d =.506.

Omnibus 2 (Group) × 3 (Video clip) ANOVAs were also conducted on self-ratings of distraction, producing a significant main effect of Group, F (1,50)= 19.070, p <.001, d =1.234, as well as a main effect of Video clip, F (2,100)= 3.446, p =.036, partial η 2 =.064 (see Table 1 ). The no movement group rated their task as less distracting than did those in the distraction group. Planned group contrasts at each level of Video clip revealed that the no movement group was significantly less distracted than the distraction group for the negative, F (1,50)=5.749, p =.020, d =.678, and the neutral video clips, F (1,50)=21.916, p <.001, d =1.323, and showed a non-significant trend in the same direction for the positive video clip.

Strategies Used

Participants in the no movement group reported a mean of 74.4 percent use of physical restriction, 5.0 percent distraction, 7.2 percent reappraisal, and 13.3 percent other in an effort to refrain from moving. Looking at each participant individually, we found that 90.5 percent of those in the no movement group reported that they used physical restriction at least half of the time. Two participants did not provide strategy estimates adding to 100 percent, and were therefore treated as not having provided strategy estimates.

The data for amount of expression were subjected to a 4 (Group) by 3 (Video clip) omnibus mixed design ANOVA. There was a main effect of Video clip, F (2,224)=34.972, p <.001, partial η 2 =.238, of Group, F (3,112)=6.731, p <.001, partial η 2 =.153, and of the interaction of Video clip by Group, F (6,224)=5.064, p <.001, partial η 2 =.119. Planned group comparisons, conducted to check that the no movement group produced less expression than the other groups, revealed that the no movement group showed less expression than the no instructions group, F (1,112) = 9.031, p =.003, d =.839, the distraction group, F (1,112) = 9.889, p =.002, d =.883, and the no instructions & no electrodes group, F (1,112) = 19.773, p <.001, d =1.265. Inspection of the means suggests that the interaction was due to substantial differences between the groups during the negative and positive video clips, but not during the neutral. Indeed, significant simple main effects of Group were seen for the negative, F (3,112)=8.865, p <.001, partial η 2 =.192, and positive video clips, F (3,112)=4.553, p =.005, partial η 2 =.109, but not for the neutral video clip.

This study sought to examine whether inhibiting facial expression influences emotional experience, particularly when participants are unaware that their facial expressions are being manipulated. Moreover, we sought to examine this relationship while controlling for the potential role of distraction due to a cognitively demanding secondary task. Overall, we found that no movement instructions, to inhibit facial expression, led participants to both show less emotion on their faces and to experience weaker emotions, whereas distraction instructions did not. This pattern held more clearly for our negative and neutral video clips, but was less clear for our positive video clip. Importantly, post-test debriefings and questionnaires indicated that participants were not aware of the experimental hypothesis, and that by a substantial margin, when asked to inhibit their expressions, participants reported attempting to physically keep their faces still rather than using some other type of regulatory strategy.

Limitations

Taken together, these results suggest that inhibiting facial expressions weakens at least some emotional experiences. In particular, this influence was most robust for the negative video clip, and less so for the neutral video clip - which itself elicited mild positive emotions. In response to our positive video clip, there were no significant differences between any of the groups. However, non-significant trends were seen in which inhibiting facial expression led to a slight decrease relative to the no instructions control group, but a slight increase as compared to both the distraction and the no instructions & no electrodes groups. Additional research is warranted examining whether the effects of inhibition of facial expression on emotional experience depends on the type or intensity of the emotion examined.

The different patterns found for the no movement and distraction groups are intriguing findings, as we might have expected a significant decrement in emotional experience as a result of the distraction instructions. The failure to find such an effect may suggest that, in at least some circumstances, a verbal secondary task does not interfere with emotional responses elicited by visual-auditory stimuli, even if it does demand attentional resources. In contrast, the no movement task specifically does interfere with the processing of at least some emotions, suggesting that processing of the type of information (e.g. verbal, visual, interoceptive, etc.) interfered with by the no movement instruction was integral to eliciting emotional responses. Testing the boundaries of this hypothesis would be an interesting direction for future research.

A second caveat in the interpretation of this study is that the non-significant results for the valence measure in the distraction condition might lead some readers to wonder whether participants were not fully engaging in the task of counting backwards. This seems unlikely, however, because the task for the distraction group was rated as more distracting than the task for the no movement group.

Conclusions & Future Directions

The research presented here provides some evidence in favor of the hypothesis that changing one’s facial expressions, in particular, inhibiting one’s facial expressions, can influence one’s emotional experience. However, this study raises at least three additional questions about the expression-experience connection that might be addressed in future work.

First, there is the issue of how well the present findings will generalize to other situations in which one might want to regulate emotion, aside from the class of situations tested. The present study examined participants’ emotional response to external stimuli, when they inhibited their facial expression as their emotional experience was developing. There may be different effects of inhibiting facial expression, for example, when changes to one’s facial expressions are attempted after one is already in an affective state, or when the emotion-eliciting stimulus is internally generated ( Duclos & Laird, 2001 ). Addressing these alternatives will help to characterize the value of inhibiting facial expression for purposes of emotion regulation.

Second, one could explore further the role of participants’ expectations regarding facial manipulations and how they might affect emotional experience. For example, researchers could explicitly provide a group of participants with a hypothesis about the effect of expressions, and investigate how doing so influences their emotional experience. Rather than probing whether facial expression, per se , can influence emotional experience, even when participants are unaware of the hypothesis, researchers could examine what happens when participants are driven towards specific beliefs regarding the process. This would further illuminate the roles cognitive processes may play in the link between expression and emotional experience.

Third, several alternative mechanisms may be at play, such as potential differences in effort, familiarity, or cultural display rules pertaining to posing or inhibiting the various facial expressions pertinent to the conditions of these studies ( Levenson & Ekman, 2002 ; Matsumoto, 2006 ). Future research can help to build on the present findings by examining whether, when, and how each of these variables might play a part.

On the whole, the present study lends support to William James and others who argued that expressions can influence emotional experience, and are not exclusively products of it. This work builds on the existing literature on the inhibition of facial expression by addressing gaps that have previously limited the interpretation of results. Until now, shifts in valence have been conflated with reductions in the magnitude of emotional experience, distraction has not been satisfactorily controlled, participants’ alternative strategies were not typically considered, and, participants may have been aware of the hypothesized effect of their own expressions. With all of these factors controlled in the present study, an impact of emotional expressions on at least some emotional experiences seems difficult to dispute.

Acknowledgments

We thank Jeremy Gray for providing some of the stimuli used, Walter Mischel for his helpful critiques of the manuscript and NIH grant MH076137 (to K.N.O) for support of this research. We also thank Rebecca Balter, Wesley Birdsall, Justin Clavadetscher, Teresa Deca, Joseph Dietzel, Samantha Kelly, Joseph Lazar, Massimo Lobuglio, Peter Mende-Siedlecki, and Lauren Pine for their assistance in conducting this research.

1 This coding method was chosen over alternatives, such as FACS ( Ekman & Friesen, 1978 ) that focus on micro-expressive changes, for two reasons. First, although methods such as FACS are very good for picking up micro-expressions, simpler methods of coding expression have proved useful in this type of work (see e.g. Gross & Levenson, 1993 , 1997 ), and the question of how micro-expressions interact with emotional experience is beyond the scope of this study. Secondly, the type of expressions that we were intending to investigate were the everyday expressions that people make. For such expressions, another socially capable person must be able to detect them if they are to be considered effectively expressive.

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Contributor Information

Joshua Ian Davis, Barnard College of Columbia University.

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Psychology Dictionary

FACIAL FEEDBACK HYPOTHESIS

was first proposed by U.S. psychologists Sylvan S. Tomkins (1911 - 1991) and Carroll F. Izard (1923 - ) as a hypothesis where afferent information from facial muscleas are dependent on intrapsychic feeling states such as anger and joy.

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Facial Feedback Hypothesis (Definition + Examples)

October 23, 2022

We show our emotions through our facial expressions. We smile when we are happy and frown when we are angry. This is one of the ways we communicate our feelings to others. But did you know it might also work the other way around? Our facial expressions can influence our emotions. 

This is the main assumption of the facial feedback hypothesis. 

What Is the Facial Feedback Hypothesis?

The facial feedback hypothesis suggests that contractions of the facial muscles communicate our feelings not only to others but also to ourselves. In other words, our facial movements directly influence our emotional state and our mood even if the circumstances around us don’t change!

facial feedback hypothesis

All humans are thought to share seven basic emotions : happiness, surprise, contempt, disgust, sadness, anger, and fear. Each one of these emotions has unique facial expressions associated with it. Raised lip corners and crow’s feet wrinkles around eyes mean joy, while tightened lips and eyebrows pulled down signify contempt. 

But facial expressions are more than just representations of our emotions. They contribute to and sustain what we are feeling. 

Example of Facial Feedback Hypothesis at Work

The best example of this theory is easy to perform. Go to the mirror and smile. Keep smiling…keep smiling! Even if you were in a bad mood before, you are likely to lighten up and maybe even start laughing! (This is much more fun to try than scowling!)

Who First Wrote About Facial Feedback Hypothesis?

The origins of facial feedback hypothesis can be traced back to the 1870s when Charles Darwin conducted one of the first studies on how we recognize emotion in faces. Darwin suggested that facial expressions of emotions are innate and universal across cultures and societies. In his book The Expression of the Emotions in Man and Animals, he argued that all humans and animals show emotion through similar behaviors. 

Paul Ekman’s Contributions to Facial Feedback Hypothesis

Numerous studies have since confirmed Darwin’s idea that facial expressions are not socially learned. Instead, they appear to be biological in nature. In the 1950s, American psychologist Paul Ekman did extensive research on facial expressions in different cultures. His findings were in line with Darwin’s idea of universality. Even the members of most remote and isolated tribes portrayed basic emotions using the same facial movements as we do.

What’s more, expressing emotions through facial movements is not any different in people who were born blind. Although they can neither see nor imitate others, they still use the same facial expressions to project their emotions as sighted people do. 

There are, however, a few exceptions. 

People with schizophrenia and individuals on the autism spectrum have not only difficulty recognizing nonverbal expressions of emotions, but also producing these spontaneous expressions themselves. They typically either remain expressionless or have looks that are hard to interpret.

The James-Lange theory of emotion

A decade after Darwin’s study, the father of American psychology William James and Danish physiologist Carl Lange proposed a new theory of emotion that has served as a basis for the facial feedback hypothesis. ​ The James-Lange Theory of Emotion implies that our facial expressions and other physiological changes create our emotions. 

physiological arousal

James famously illustrated this assertion with a story of a man being chased by a bear. A man is unfortunate enough to encounter a bear in a forest. He is afraid and, naturally, his heart races and he is sweating as he starts running away. According to the psychologist, it is precisely these physiological changes that provoke the man’s feeling of fear. In other words, he doesn’t run from the bear because he is afraid. He is afraid because of his physiological response to running away. 

Fritz Strack’s cartoon experiment

In 1988, German psychologist Fritz Strack and his colleagues conducted a well-known experiment to demonstrate the facial feedback hypothesis. The participants in Strack’s experiment were instructed to look at cartoons and say how funny they thought these cartoons were. They were asked to do this while holding a pen in their mouths. Some participants held the pen with their lips, which pushed the face into a frown-like expression. Others held it with their teeth, forcing a smile. 

Strack’s results were in line with the facial feedback hypothesis and were since confirmed by several other studies. The participants who used a pen to mimic a smile thought that the cartoons were funnier than those who were frowning. The participants’ emotions were clearly influenced by their facial expressions. 

Characteristics of Facial Feedback

The brain is hardwired to use the facial muscles in specific ways in order to reflect emotions. When contracted, facial muscles pull on the skin allowing us to produce countless expressions ranging from frowning to smiling, raising an eyebrow, and winking. In fact, we are capable of making thousands of different facial expressions, each one lasting anywhere between ​ 0.5 seconds (microexpressions) to 4 seconds. 

universal expressions

But facial expressions can indicate various degrees of emotions as well. When we are slightly angry, we display only a light frown and somewhat furrowed eyebrows. If we are furious, our expression becomes more distinctive. In addition, we can show combinations of different emotions through subtle variations of our facial movements.

The facial feedback hypothesis has the strongest effect when it comes to modulation, that is, intensifying our existing feelings rather than initiating a completely new emotion. 

Modulating also means that if we avoid showing our emotions using our facial muscles we will, as a consequence, experience a weaker emotional response. We won’t feel the emotions as strongly as we otherwise would. The lack of facial expressions or inhibition of these expressions lead to the suppression of our emotional states. 

Applications of the Facial Feedback Hypothesis

The facial feedback phenomenon has several possible applications. It can help us be more positive, have better control of our emotions, and strengthen our feelings of empathy. We can simply use the facial feedback hypothesis to make us feel better in situations that we would rather avoid. If we force a smile instead of frowning at a boring event, for example, we may actually start to enjoy ourselves a bit more. We can use the same exercise whenever we are feeling overwhelmed, powerless, or stressed. 

Research shows that regulating emotions through facial feedback can have positive outcomes in areas ranging from psychotherapy to child education and endurance performances.

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  • Facial Expressions of Emotions (Microexpressions)
  • James-Lange Theory of Emotion (Definition + Examples)
  • Two Factor Theory of Emotion

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Theodore is a professional psychology educator with over 10 years of experience creating educational content on the internet. PracticalPsychology started as a helpful collection of psychological articles to help other students, which has expanded to a Youtube channel with over 2,000,000 subscribers and an online website with 500+ posts.

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facial feedback hypothesis def

Cannon-Bard Theory of Emotion: Definition and Examples

Charlotte Nickerson

Research Assistant at Harvard University

Undergraduate at Harvard University

Charlotte Nickerson is a student at Harvard University obsessed with the intersection of mental health, productivity, and design.

Learn about our Editorial Process

Saul Mcleod, PhD

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BSc (Hons) Psychology, MRes, PhD, University of Manchester

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On This Page:

Key Takeaways

  • The primary argument of the Cannon-Bard theory of emotion is that emotions trigger affective “feelings” and physiological responses to stimuli simultaneously in different regions of the brain. This stands in contrast to the James-Lange theory of emotion, which posits that people and animals feel emotions because they consciously process their physiological responses to stimuli.
  • The Cannon-Bard theory of emotion differentiates between feelings associated with the sympathetic nervous system (fight or flight responses) and the parasympathetic nervous system (calm responses), and Cannon believed that sympathetic and parasympathetic responses could not happen simultaneously.
  • The Cannon-Bard and James Lange theories of emotion have greatly influenced modern research into emotional processing and the brain; however, both theories have garnered great criticism for their overgeneralization of emotion and contradictions between theory and evidence dating as far back as Cannon’s own research.

thalamus

According to Cannon-Bard theory of emotion, physiological arousal and emotional experience occur simultaneously, yet independently. This theory was proposed in the 1920s and early 1930s by Walter B. Cannon and Philip Bard.

In short, the Cannon-Bard theory of emotion, also known as the Thalamic theory of emotion, states that the lower part of the brain, what neurologists call the thalamus , controls emotional experience.

Meanwhile, the higher part of the brain, the cortex , controls emotional expression. These feelings (through the thalamus) and physical reactions (through the cortex) occur at the same time. For example, seeing a spider may trigger both a physical response (such as jerking back one’s hand) and an affective, emotional one (such as a feeling of fear).

The Cannon-Bard Theory of Emotion represented a shift from the James-Lange Theory of emotion to one which studied central brain mechanisms as the cause of emotions; however, work as far back as the 1860s posited physiological causes for emotion (Dror, 2014).

How Does the Cannon-Bard Theory Work?

The main idea of Cannon’s approach to emotions is that people react to emotional stimuli but that two separate parts of the brain control the conscious feeling of emotion and the body’s physiological response.

Cannon reviewed research on emotions in both animals and people with brain damage, as well as conducted his own experiments. He concluded that the thalamus was the brain region most involved in physiological emotion, while the cortex is responsible for controlling and inhibiting it.

This is supported by modern neuroscience, which believes that the thalamus is responsible for relaying sensory and motor signals to the cerebral cortex, which handles processes related to thought, consciousness, reasoning, and memory.

Stressful Exam

Say that a student is about to take a high-stakes midterm exam that he has not studied for. This stressful stimulus (an upcoming exam) triggers two brain regions separately: the cortex and the thalamus.

The cortex triggers a physiological response to the emotion. For example, the student may be sweating, his heart may race, and his fingers may tremble as he picks up his pencil.

According to the Cannon-Bard theory of emotion, these are physiological responses to stress triggered by the sympathetic nervous system, and the triggering of the sympathetic nervous system means that the parasympathetic nervous system cannot be triggered.

Meanwhile, the stimulus triggers the student’s thalamus separately, leading to the conscious, affective feeling of stress.

The student is not stressed because he is trembling, according to Cannon-Bard, but because his thalamus has been activated by an impending exam.

This emotional reaction would be separate and independent of the physiological arousal, even though they co-occur.

Purring Cat

Taking an example from Bard’s 1936 letter to Cannon, consider a resting cat who is being petted by its owner. As the owner pets the cat, the cat may purr and relax its muscles or slowly fall asleep.

This purring is a physiological response of the parasympathetic nervous system to the stimulus of being a pet, and, according to the Cannon-Bard theory of emotion, exists entirely separately from the cat perceiving a conscious emotion (such as calmness or comfort).

According to the Cannon-Bard theory of emotion, the cat is not calm because it is purring and has relaxed muscles; rather, it is calm because the stimulus of petting has activated its thalamus, allowing the cat to have the conscious, affective emotion of calm.

Comparison to Other Theories

James-Lange theory of emotion came to influence a century of empirical emotional research and rebuttals of the James-Lange theory of emotion, notably Cannon-Bard’s 1927 critique, have spurned long-standing debates in neuroscience and psychology (Lang, 1994).

James-Lange Theory of Emotion

Both the James-Lange and Cannon-Bard Theories of emotion investigated whether emotions originated from a source central or peripheral to the nervous system (Meiselman, 2016).

The James-Lange theory of emotion is ultimately a peripheral approach to understanding emotion. This means that rather than first perceiving some stimulus that could elicit an emotion, experiencing an emotion, and then experiencing some bodily reaction in response, James-Lange assumes that the bodily reactions themselves elicit conscious emotions.

Cannon offers five objections to the James-Lange theory of emotion:

1.) The latency of physiological responses to emotion is too long to account for the immediacy of emotional behavior;

2.) Artificially inducing bodily reactions to emotion does not in itself produce emotions;

3.) The viscera are so-called “insensitive structures;”

4.) Visceral changes are the same between emotions and

5.) Interrupting the feedback that occurs because of visceral bodily emotions does not influence emotional behavior (Fehr and Stern, 1970).

To illustrate the contrast from which these five objections arise, consider somebody who is afraid of dogs. The dog barks within range of the person, and the person is aroused, according to the James-Lange theory of emotion, autonomically.

This person could have a physical response such as trembling. Because of that autonomic arousal (the trembling), the person has a conscious feeling of fear. The person feels afraid because they tremble.

Meanwhile, according to the Cannon-Bard theory of emotion, the dog’s bark triggers two separate regions of the brain: the thalamus and the cortex.

Because the dog triggers the cortex, which controls physical reactions, the person trembles. However, the person feels fear because the bark triggers the thalamus, which controls the conscious feelings of emotion.

In theory, if that person’s thalamus or cortex were dysfunctional, the person may be able to feel fear without trembling or tremble without feeling fear. The dog makes the person tremble and feel afraid, but these are reactions stemming from two entirely different parts of the brain.

Considering his objections, Canon introduced a specificity model of emotions (Dror, 2014). He distinguished different classes of emotions by whether they affected the sympathetic or parasympathetic nervous system.

Emotions that affect the sympathetic nervous system are associated with fight or flight responses , and those that activate the parasympathetic nervous system restore the body to a state of calm (Waxenbaum, 2021). The anatomical, physiological, and metabolic differences between the emotions expressed by the sympathetic and parasympathetic nervous systems create a difference in how people consciously label these emotions (Cannon, 1914).

In contrast to the Cannon-Bard and James-Lange theories of emotion, the so-called “common sense” theory of emotion posits that someone has an emotional response, and this response triggers a physiological reaction.

For example, someone can see a barking dog and consciously feel fear. As a result, they tremble (Meiselman, 2016).

Singer’s Two-Factor Theory of Emotion

In the Schachter-Singer Two Factor Theory of Emotion , one does a conscious cognitive appraisal of their physiological response, labels that response, and feels the emotion that results. Neither physiological nor cognitive arousal in itself is enough to elicit an emotion, according to Schacter-Singer.

The Cannon-Bard theory maintains that emotional experience occurs simultaneous to and independent of physiological arousal.

The Schachter-Singer two-factor theory suggests that physiological arousal receives cognitive labels as a function of the relevant context and that these two factors together result in an emotional experience.

To repeat the example of a barking dog, a person may tremble or feel an increased heart rate. After detecting that they are trembling, the person can then label the physiological response (“I must be scared!”) and only then consciously feel the emotion.

A person, according to the Two Factor Theory of Emotion, must appraise their physiological responses in order to experience emotion (Meiselman, 2016).

Zajonc-LeDoux Theory of Emotion

The Zajonc-LeDoux theory of emotion says that emotional reactions exist separately from cognitive labels on emotional situations.

According to this theory, some emotions that have evolutionarily been necessary (e.g., anger or fear) are activated through quicker pathways than others.

Certain emotions can happen instantly without an active cognitive appraisal. For example, someone can be startled by the bark of a dog before labeling it as a threat (Meiselman, 2016).

Key Research

In 1925, Cannon and Britton introduced a way of studying emotions through a cat whose cortex had been removed from his brain (Cannon and Britton, 1925).

From this cat, Cannon and Britain described a new type of emotion — “sham rage.”

At the time, Cannon noticed that laboratory animals did not consistently develop the desired emotional reactions to stimuli consistently and dependently, so Cannon removed the region of the brain — the cortex — thought to inhibit emotions, allowing Cannon to study a stream of emotions over longer periods of time.

This decorticated cat came to underpin Cannon’s physiological model of emotional experience.

In the mid-1920s, Philip Bard was a doctoral student studying under Walter Bradford, a physiologist at Harvard University, and two years after introducing this method for studying the physiology of emotions, Cannon suggested that Philip Bard section the cat’s brain in order to discover which parts of the brain were responsible for emotional expression (Bard, 1973).

From this, Cannon-Bard discovered that the thalamus generated affective emotions.

Many neurologists have initiated empirical research in order to determine how and in which order emotion affects various regions of the body.

The first of these researchers was Allport, who devised the facial feedback hypothesis (Laird, 1984). In short, the facial feedback hypothesis postulated that one’s facial expressions directly affect one’s emotional experience. For example, someone who tries to smile will feel happier because they have a smiling expression.

To Tomkins (1962-1963), emotions are “sets of muscles and glandular responses located in the face.”

Later, researchers suggested embodied theories of emotion. According to embodied theories of emotion, simply contracting the facial muscles associated with a particular emotion can intensify or elicit the emotion associated with those contractions, even when participants are not contracting those muscles consciously (Niedenthal, 2007; Soussignan, 2002).

Cannon (1927) conducted several animal tests to disprove James-Lange’s peripheralist approach to emotion (Meiselman, 2016). For example, Cannon conducted tests where he artificially induced certain bodily reactions and observed that these in themselves did not elicit emotions (Meiselman, 2016).

Researchers such as Fehr and Stern (1970), among many others, have criticized these tests. One of the predominant criticisms of the Cannon-Bard Theory of Emotion is that the theory assumes that physical reactions do not influence emotions.

For example, Cannon-Bard would assume that someone would not necessarily feel happy if the facial muscles creating a smile were triggered.

However, a large body of research on facial expressions and emotions suggests that this assumption is not true.

Some scholars, such as Dror (2014), have argued that Cannon’s own studies have contradicted his theory of emotion.

For example, one large component of Cannon’s physiological theory of emotion was the belief that either the sympathetic or parasympathetic nervous system could be activated by emotion, but the activation of these systems was mutually exclusive.

Relatively common phenomena — such as the contraction of the bladder and rectum during intense emotional stress — would confuse Cannon and his followers because these represented the simultaneous activation of the sympathetic and parasympathetic nervous systems (Cannon, 1914).

Scholars, and indeed Cannon himself, were aware of contradictions and flaws in his studies of the decorated cat as a model for physiological and emotional experience (Dror, 2014).

For example, as Dror (2014) emphasizes, Cannon and Britton included clear evidence of parasympathetic activation, such as contraction of the rectum and occasionally defecation, in their descriptions of the cat experiencing “sham rage” – a supposedly sympathetic, fight or flight emotion (Cannon and Britton, 1925).

Many other physiologists in the 1930s would confirm this evidence that “shame rage” activated both the sympathetic and parasympathetic nervous systems (Beattie, 1932; Beebe-Center and Stevens, 1938).

The second major flaw of Cannon’s theory, according to Dror’s 2014 review, was that there was a lack of anatomical proof for two major aspects of the Cannon-Bard theory of emotion.

The stipulation of the Cannon-Bard model that the optic thalamus was the region that organized emotional expressions, as well as the belief that the thalamus itself was the source of the affective experience of emotion, lacked anatomical proof (Cannon, 1927).

Thirdly and lastly, scholars have criticized Cannon’s theory for its overextension beyond the evidence provided by the Cannon-Bard experiments.

Although Cannon-Bard studied the decoriated cat’s “sham rage” exclusively, Cannon would go on to extend his model of emotions to joy, grief, and disgust long before Philip Baard himself would send a letter to Cannon observing pleasure in decorticated cats (such as pleasure when being petted) (Dror, 2014).

Bard, P. (1973). The ontogenesis of one physiologist. Annual Review of Physiology, 35 (1), 1-16.

Beattie, J. (1932). Hypothalamic mechanisms. Canadian Medical Association Journal, 26(4), 400.

Beebe-Center, J., & Stevens, S. (1938). The emotional responses: changes of heart-rate in a gun-shy dog. Journal of Experimental Psychology, 23 (3), 239.

Bernard, C. (1866). Leçons sur les propriétés des tissus vivants: Germer Baillière.

Cannon, W. B. (1914). The interrelations of emotions as suggested by recent physiological researches. The American Journal of Psychology, 25 (2), 256-282.

Cannon, W. B. (1927). The James-Lange theory of emotions: A critical examination and an alternative theory. The American Journal of Psychology, 39 (1/4), 106-124.

Cannon, W. B., & Britton, S. W. (1925). Studies on the conditions of activity in endocrine glands: XV. Pseudaffective medulliadrenal secretion. American Journal of Physiology-Legacy Content, 72 (2), 283-294.

Coppin, G., & Sander, D. (2021). Chapter 1 – Theoretical approaches to emotion and its measurement. In H. L. Meiselman (Ed.), Emotion Measurement (Second Edition) (pp. 3-37): Woodhead Publishing.

Dalgleish, T., Dunn, B. D., & Mobbs, D. (2009). Affective neuroscience: Past, present, and future. Emotion Review, 1 (4), 355-368.

Darwin, C. (1872). The expression of the emotions in man and animals by Charles Darwin: John Murray.

de Cyon, E. (1873). Principes d”électrothérapie: Baillière.

Dror, O. E. (2013). The Cannon–Bard Thalamic Theory of Emotions: A Brief Genealogy and Reappraisal. Emotion Review, 6 (1), 13-20. doi:10.1177/1754073913494898

Durant, J. R. (1981). The beast in man: An historical perspective on the biology of human aggression. The biology of aggression, 17-46.

Ellsworth, P. C. (1994). William James and emotion: is a century of fame worth a century of misunderstanding? Psychological Review, 101 (2), 222.

Fehr, F. S., & Stern, J. A. (1970). Peripheral physiological variables and emotion: the James-Lange theory revisited. Psychological Bulletin, 74 (6), 411.

Friedman, B. H. (2010). Feelings and the body: The Jamesian perspective on autonomic specificity of emotion. Biological Psychology, 84 (3), 383-393.

Laird, J. D. (1984). The real role of facial response in the experience of emotion: a reply to Tourangeau and Ellsworth, and others.

Lanska, D. J. (2014). Cannon, Walter Bradford. In M. J. Aminoff & R. B. Daroff (Eds.), Encyclopedia of the Neurological Sciences (Second Edition) (pp. 580-583). Oxford: Academic Press.

Meiselman, H. L. (2016). Emotion measurement: Woodhead publishing.

Niedenthal, P. M. (2007). Embodying emotion. Science, 316 (5827), 1002-1005.

Sherrington, C. S. (1900). Experiments on the value of vascular and visceral factors for the genesis of emotion. Proceedings of the Royal Society of London, 66 (424-433), 390-403.

Soussignan, R. (2002). Duchenne smile, emotional experience, and autonomic reactivity: a test of the facial feedback hypothesis. Emotion, 2 (1), 52.

Tomkins, S. (1963). Affect imagery consciousness: Volume II: The negative affects: Springer publishing company.

Waxenbaum, J. A., Reddy, V., & Varacallo, M. (2019). Anatomy, autonomic nervous system.

Further Information

Cannon, W. B. (1927). The James-Lange theory of emotions: A critical examination and an alternative theory. The American journal of psychology, 39(1/4), 106-124.

Cannon, W. B. (1914). The interrelations of emotions as suggested by recent physiological researches. The American Journal of Psychology, 25(2), 256-282.

Barrett, L. F. (2012). Emotions are real. Emotion, 12(3), 413.

Ellsworth, P. C. (1994). William James and emotion: is a century of fame worth a century of misunderstanding?. Psychological review, 101(2), 222.

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Nonverbal behavior and the theory of emotion: the facial feedback hypothesis

  • PMID: 7381683
  • DOI: 10.1037//0022-3514.38.5.811

The facial feedback hypothesis, that skeletal muscle feedback from facial expressions plays a causal role in regulating emotional experience and behavior, is an important part of several contemporary theories of emotion. A review of relevant research indicates that studies reporting support for this hypothesis have, without exception, used within-subjects designs and that therefore only a restricted version of the hypothesis has been tested. Also, the results of some of these studies must be questioned due to demand characteristics and other problems. It is suggested that visceral feedback may make a more direct contribution to emotional processes than facial feedback does and that the "readout" functions of facial expressions are more important than any feedback functions.

  • Emotions / physiology*
  • Facial Expression*
  • Facial Muscles / physiology*
  • Nonverbal Communication

Your Facial Expressions Can Impact Your Mood

Facial Feedback History

Theories on the facial feedback effect.

facial feedback hypothesis def

Charles Darwin and William James are credited for the concepts that led to the facial feedback hypothesis . Darwin claimed that enhancing or inhibiting an emotional expression would alter the intensity of the emotional experience (Darwin, 1872). James proposed an even stronger correlation and indicated that the face could have an  initiating  role in the experience of emotion (James, 1884), which instigated a debate on the subject that lasted decades. By the mid-twentieth century, most psychologists believed that facial expression could only  modulate  an emotional experience (Allport, 1922; Gellhorn, 1964). However, some psychologists came to support an  initiating  role over time, as James had proposed (Strack et al., 1988; Levenson, Ekman, & Friesen, 1990; Soussignan, 2002).

Facial Feedback Research

The term facial feedback was coined in the 1960s, and in the 1970s, 80s, and 90s experimental studies of the FFH flourished, with most yielding data indicating facial feedback’s role in emotion processes (McCanne & Anderson, 1987). During the 21st century, FFH studies have continued, many utilizing modern technologies such as electromyography (EMG), electroencephalography (EEG), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) to more objectively quantify facial expressions and neural activity, providing a basis for the hypothesized relationships.

More Facial Feedback Hypotheses

Tourangeau and Ellsworth (1979) identified three potential explanations for the Facial Feedback Hypothesis:

  • The necessity hypothesis suggests that facial expression must be present for a subjective emotional experience;
  • The sufficiency hypothesis proposes a facial expression is sufficient to initiate an emotional experience;
  • The monotonicity hypothesis suggests that the intensity of facial expression will have a positive, monotonic (unchanging) correlation with the intensity of the subjective emotion.

To test their hypotheses, Tourangeau and Ellsworth had 123 college students tighten specific facial muscles to create a facial expression typical for either fear, sadness, or a non-emotional grimace while watching a two-minute film eliciting fear, sadness, or no emotion. Subjects then reported their subjective fear and sadness. Results showed that the subject of the film affected the student’s self-reported ratings of fear and sadness (P < 0.05 for each), while only a very slight correlation was found between manipulated facial expression and self-reported fear (r = 0.01) and sadness (r = 0.02).

Tourangeau and Ellsworth’s study results did not support the facial feedback hypothesis ; however, their study was later criticized by Izard (1981) for multiple flaws in the premise (e.g., ignoring the impact of covert facial expressions, possible differences in physiological responses in voluntary and involuntary facial expressions) and protocol (e.g., the effort of holding a pose for two minutes; incongruence between sensory stimuli and face; insufficient diversity in self-report scales). Nevertheless, their suggested terms would help frame future FFH research, which included studying natural facial expressions during emotional states (Hess et al., 1992), studying emotions created by manipulated facial expressions (Strack et al., 1988; Levenson, Ekman, & Friesen, 1990; Soussignan, 2002), and suppressing or enhancing facial displays during emotionally arousing stimuli (McCanne & Anderson, 1987; Lee et al., 2012).

The sufficiency and monotonicity-based FFH hypotheses have been researched more thoroughly and are generally supported (Strack et al., 1988; Soussignan, 2002; Lewis, 2012), while the necessity hypothesis has been less researched and accepted (Fernández-Dols & Ruiz-Belda, 1995). Additional FFH research has examined discrete emotions (e.g., anger, fear, happiness) versus dimensional (e.g., valence and arousal) (Adelmann & Zajonc, 1989; Soussignan, 2004) and the subject’s awareness of facial manipulation (Strack, 1988; Larsen et al., 1992; Soussignan, 2002).

Questions or comments? We would love to hear from you.

facial feedback hypothesis def

Adelmann, P. K., & Zajonc, R. B. (1989). Facial efference and the experience of emotion.  Annual Review of Psychology ,  40 (1), 249–280. https://doi.org/10.1146/annurev.ps.40.020189.001341

Allport, F. H. (1922). A physiological-genetic theory of feeling and emotion. Psychological Review, 29, 132–139. http://dx.doi.org/10.1037/h0075652

Darwin, C. (1872). The expression of the emotions in man and animals . London, UK: William Clowes and Sons.

Fernández-Dols, J. M., & Ruiz-Belda, M. A. (1995). Are smiles a sign of happiness? Gold medal winners at the Olympic Games. Journal of Personality and Social Psychology, 69, 1113–1119. https://doi.org/10.1037/0022-3514.69.6.1113

Gellhorn, E. (1964). Motion and emotion: The role of proprioception in the physiology and pathology of the emotions. Psychological Review, 71, 457–472. http://dx.doi.org/10.1037/h0039834

Hess, U., Kappas, A., McHugo, G. J., Lanzetta, J. T., & Kleck, R. E. (1992). The facilitative effect of facial expression on the self-generation of emotion. International Journal of Psychophysiology, 12 (3), 251–265. https://doi.org/10.1016/0167-8760(92)90064-I

James, W. (1884). What is an emotion? Mind, 9, 188–205. http://dx.doI.org/10.1093/mInd/os-IX.34.188

Levenson, R.W., Ekman, P., & Friesen, W. V. (1990). Voluntary facial action generates emotion-specific autonomic nervous system activity. Psychophysiology, 27 , 363–384. https://doi.org/10.1111/j.1469-8986.1990.tb02330.x

McCanne, T., & Anderson, J. A. (1987). Emotional Responding Following Experimental Manipulation of Facial Electromyographic Activity. Journal of Personality and Social Psychology, 52(4), 759–768. https://doi.org/10.1037/0022-3514.52.4.759

Soussignan, R. (2002). Duchenne smile, emotional experience, and autonomic reactivity: A test of the facial feedback hypothesis. Emotion, 2 (1), 52–74. https://doi.org/10.1037/1528-3542.2.1.52

Strack, Martin, L. L., & Stepper, S. (1988). Inhibiting and facilitating conditions of the human smile.  Journal of Personality and Social Psychology ,  54 (5), 768–777. https://doi.org/10.1037/0022-3514.54.5.768

Tourangeau, R. & Ellsworth, P. C. (1979). The role of facial response in the experience of emotion.  Journal of Personality and Social Psychology ,  37 (9), 1519–1531. https://doi.org/10.1037/0022-3514.37.9.1519

IMAGES

  1. Facial Feedback Hypothesis (Definition + Examples)

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  2. Facial Feedback Hypothesis (Definition + Examples)

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  3. The Facial Feedback Hypothesis

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COMMENTS

  1. Facial Feedback Hypothesis (Definition

    The facial feedback hypothesis suggests that contractions of the facial muscles communicate our feelings not only to others but also to ourselves. In other words, our facial movements directly influence our emotional state and our mood even if the circumstances around us don't change!

  2. What Is The Facial Feedback Hypothesis And Does It Work?

    The facial feedback hypothesis states that our facial expressions affect our emotions. If the facial-feedback hypothesis is correct, then not only do we smile when we feel happy, but smiling can make us feel happy, too. According to this hypothesis, in these cases, it is the act of smiling that produces a happy feeling.

  3. Facial feedback hypothesis

    The facial feedback hypothesis, rooted in the conjectures of Charles Darwin and William James, is that one's facial expression directly affects their emotional experience.

  4. How the Experience of Emotion is Modulated by Facial Feedback

    The facial feedback hypothesis is based on the idea that a facial expression not only expresses an emotion, but also that expression and experience are linked in that afferent sensory feedback from the facial action influences the emotional experience. Elevating your cheeks can make you happier, just as furrowing your brow can make you angrier.

  5. James-Lange Theory of Emotion: Definition and Examples

    William James' (1884) theory of emotion proposed that there are a set of basic emotions (such as anger) and that each of these emotions has its own associated physical state (emotional measurement).

  6. Facial-Feedback Hypothesis

    The facial-feedback hypothesis states that the contractions of the facial muscles may not only communicate what a person feels to others but also to the person him- or herself. In other words, facial expressions are believed to have a direct influence on the experience of affect.

  7. A multi-lab test of the facial feedback hypothesis by the Many Smiles

    Following theories of emotional embodiment, the facial feedback hypothesis suggests that individuals' subjective experiences of emotion are influenced by their facial expressions. However,...

  8. Facial feedback hypotheses: Evidence, implications, and directions

    This review evaluates four facial feedback hypotheses, each proposing a certain relation between the face and emotions. It addresses criticisms of the data, considers implications for emotional and social processes, and advises directions for future research. The current data support the following: Facial actions are sensitive to social context, yet correspond to the affective dimension of ...

  9. Nonverbal behavior and the theory of emotion: The facial feedback

    The facial feedback hypothesis (skeletal muscle feedback from facial expressions plays a causal role in regulating emotional experience and behavior) is an important part of several contemporary theories of emotion.

  10. PDF A Meta-Analysis of the Facial Feedback Literature

    The facial feedback hypothesis suggests that an individual's experience of emotion is influenced by feedback from their facial movements. To evaluate the cumulative evidence for this hypothesis, we conducted a meta-analysis on 286 effect sizes derived from 138 studies that manipulated facial feedback and collected emotion self-reports.

  11. University of Texas at Tyler Scholar Works at UT Tyler

    The facial feedback hypothesis (FFH) is the idea that, in addition to being affected. by. emotion, facial expressions actually affect emotion (Hess & Thibault, 2009). For instance, smiling has the power to make the person happy, whether they felt happy in the first place or not. While the veracity of FFH in the general population has been called

  12. How Does Facial Feedback Modulate Emotional Experience?

    Other research on how generating facial expressions can modulate emotional experience that is in response to stimuli tends to support these findings (for reviews see Adelman and Zajonc, 1989, Capella, 1993, Laird 1984, Matsumoto, 1987, McIntosh, 1996, and Soussignan, 2004 ). In general, smiling makes a person feel more positive, and frowning ...

  13. Facial feedback hypotheses: Evidence, implications, and directions

    The facial feedback hypothesis states that feedback from cutaneous and muscular afferents affects our emotion. Based on the facial feedback hypothesis, the purpose of this study was to determine ...

  14. FACIAL FEEDBACK HYPOTHESIS

    was first proposed by U.S. psychologists Sylvan S. Tomkins (1911 - 1991) and Carroll F. Izard (1923 - ) as a hypothesis where afferent information from facial muscleas are dependent on intrapsychic feeling states such as anger and joy. ID, 'custom_sentence', true); if (!empty ($custom_sentence)) { ?> : " " [cite] Share this Article By N., Sam M.S.

  15. Theories of Emotion

    The facial-feedback hypothesis asserts that facial expressions and emotional state are connected, based on the ideas of Charles Darwin and William James. Both believed that physiological responses ...

  16. Facial Feedback Hypothesis (Definition + Examples)

    The facial feedback hypothesis suggests that contractions of the facial muscles communicate our feelings not only to others but also to ourselves. In other words, our facial movements directly influence our emotional state and our mood even if the circumstances around us don't change!

  17. How the experience of emotion is modulated by facial feedback

    The facial feedback hypothesis states that facial actions modulate subjective experiences of emotion. Using the voluntary facial action technique, in which the participants react with instruction induced smiles and frowns when exposed to positive and negative emotional pictures and then rate the pleasantness of these stimuli, four questions were addressed in the present study. The results in ...

  18. PDF Nonverbal Behavior and the Theory of Emotion: The Facial Feedback

    The facial feedback hypothesis, that skeletal muscle feedback from facial expres- sions plays a causal role in regulating emotional experience and behavior, is an important part of several ...

  19. Cannon-Bard Theory of Emotion: Definition and Examples

    The first of these researchers was Allport, who devised the facial feedback hypothesis (Laird, 1984). In short, the facial feedback hypothesis postulated that one's facial expressions directly affect one's emotional experience. For example, someone who tries to smile will feel happier because they have a smiling expression.

  20. Nonverbal behavior and the theory of emotion: the facial feedback

    The facial feedback hypothesis, that skeletal muscle feedback from facial expressions plays a causal role in regulating emotional experience and behavior, is an important part of several contemporary theories of emotion.

  21. Facial Feedback History

    Charles Darwin and William James are credited for the concepts that led to the facial feedback hypothesis. Darwin claimed that enhancing or inhibiting an emotional expression would alter the intensity of the emotional experience (Darwin, 1872). James proposed an even stronger correlation and indicated that the face could have an initiating role ...

  22. Facial Feedback Theory definition

    The Facial Feedback Theory holds that facial movement and expressions can influence attitude and emotional experience. For instance, when a person attends a function and is required to smile for the duration of the function, they will actually have a better experience of the function. Add flashcard Cite Random Word of the Day