facial feedback hypothesis psychology definition

Facial Feedback Hypothesis (Definition + Examples)

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!

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. 

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. 

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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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.

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.

Facial Feedback Hypothesis: The Power of Facial Expressions in Shaping Emotions

The facial feedback hypothesis is a fascinating concept in psychology that suggests our facial expressions can influence our emotions. According to this theory, when we smile, it not only reflects happiness but also has the power to actually make us feel happier. Similarly, frowning might intensify feelings of sadness or anger.

This hypothesis proposes that our facial muscles send signals to our brain, which then interprets those signals and triggers corresponding emotional responses. By altering our facial expressions, we may be able to manipulate and regulate our emotions to some extent.

Research into the facial feedback hypothesis has yielded intriguing results. For example, studies have shown that participants who held a pen between their teeth (which activates the smiling muscles) rated cartoons as funnier compared to those who held a pen between their lips (which inhibits smiling). These findings suggest a strong connection between facial expressions and emotional experience.

Understanding the impact of facial feedback on emotions can have important implications for various fields such as therapy, communication, and even daily interactions. By recognizing how our own expressions affect our mood and considering the influence of others’ expressions on their emotions, we can enhance empathy and improve interpersonal relationships.

In conclusion, the facial feedback hypothesis proposes that there is a bidirectional relationship between our facial expressions and emotions. The way we use or modify our faces can potentially shape how we feel internally. As I delve deeper into this topic, let’s explore the research behind this intriguing theory and its practical applications in more detail.

What is the Facial Feedback Hypothesis?

The Facial Feedback Hypothesis suggests that our facial expressions can influence and even shape our emotions. According to this hypothesis, when we make certain facial expressions, such as smiling or frowning, it can trigger corresponding emotional responses within us. In other words, our facial muscles send signals to our brain that then impact how we feel.

For example, have you ever noticed that when you force yourself to smile, even if you’re not feeling particularly happy at the moment, you start to feel a bit better? This phenomenon aligns with the Facial Feedback Hypothesis. By activating the muscles associated with smiling, your brain receives feedback that there may be something positive happening and responds by releasing feel-good chemicals like endorphins.

On the other hand, furrowing your brow or scowling might lead to feelings of anger or frustration. The tension in these facial muscles sends signals to your brain that something negative is occurring, which can intensify those negative emotions.

Research has shown various interesting findings related to the Facial Feedback Hypothesis. One study conducted by psychologist Fritz Strack and colleagues in 1988 involved participants holding a pen either between their teeth (forcing a smile-like expression) or between their lips (preventing any significant facial movement). The participants who held the pen between their teeth reported finding cartoons funnier compared to those who held it between their lips. This experiment provided evidence supporting the idea that facial expressions can impact emotional experiences.

Another study published in 2012 by Joshua Davis and Ann Senghas explored how altering participants’ facial expressions affected their emotional reactions while watching emotionally charged videos. Participants were instructed to either hold chopsticks with their teeth (creating a smile-like expression) or hold them with their lips (creating a frown-like expression). Interestingly, those who held the chopsticks with their teeth reported feeling more positive emotions than those who held them with their lips.

These studies and others like them demonstrate the potential power of facial expressions in shaping our emotional experiences. While there is still much to learn about the intricacies of this hypothesis, it offers intriguing insights into the connection between our facial muscles and our emotions. It highlights the idea that our expressions not only reflect how we feel but also have the ability to influence how we feel.

The Role of Facial Expressions in Emotion

When it comes to understanding human emotions, facial expressions play a crucial role. Our faces are not only a canvas for displaying our feelings but also an essential means of communication. The facial feedback hypothesis suggests that the expressions we make with our faces can actually influence and even intensify our emotional experiences.

Think about it – when you’re feeling joyful, your face naturally lights up with a smile. But what if I told you that the reverse is also true? That by intentionally putting on a smile, you can actually boost your mood and experience genuine happiness? It may sound surprising, but research has shown that simply forcing yourself to smile can lead to increased positive emotions.

A classic study conducted by psychologist Paul Ekman found that participants who held a pen between their teeth (forcing them into a smiling expression) while watching cartoons reported greater amusement compared to those who held the pen with their lips (preventing them from smiling). This demonstrates how our facial expressions can influence the way we perceive and interpret emotions.

Furthermore, studies have indicated that specific facial expressions may be universally recognized across different cultures. For example, furrowed brows and tight lips typically convey anger or frustration, while raised eyebrows and widened eyes often indicate surprise or fear. These universal expressions suggest an innate connection between facial movements and emotional states.

In addition to influencing our own emotions, facial expressions also play a vital role in social interactions. They serve as nonverbal cues that help us understand the emotional states of others and enable empathy and effective communication. Imagine trying to navigate through life without being able to read subtle changes in someone’s face – it would certainly make understanding others’ feelings much more challenging.

In conclusion, the role of facial expressions in emotion cannot be underestimated. Our faces act as powerful tools for both expressing and experiencing emotions. By recognizing the impact of our own facial expressions on our emotional well-being, we can harness this knowledge to shape our moods and enhance our interpersonal connections. So, the next time you find yourself in need of a mood boost, try putting on a smile – it might just make all the difference.

The Connection between Facial Feedback and Mood

Let’s dive into the fascinating connection between facial feedback and mood. It’s truly intriguing how our facial expressions can influence our emotional state. As we explore this topic further, you’ll discover the impact that simple facial movements can have on shaping our moods.

Have you ever noticed that when you smile, even if it’s forced, you start to feel a little bit happier? That’s because our facial muscles send signals to our brain, triggering the release of neurotransmitters associated with positive emotions. So, by simply putting on a smile, even when we’re not genuinely happy, we can actually boost our mood.

On the flip side, frowning or expressing negative emotions through our facial expressions can have the opposite effect. When we furrow our brows or tighten our jaw in frustration or sadness, it sends signals to the brain that reinforce those negative feelings. This is why sometimes we find ourselves feeling even more down when we allow ourselves to dwell on negative thoughts.

To illustrate this connection between facial feedback and mood, let me share an interesting study conducted at a university campus. Researchers asked participants to hold a pencil horizontally in their mouths without letting their lips touch it – essentially simulating a smile – while watching funny videos. Surprisingly, those who held the pencil in this way reported finding the videos funnier compared to those who held it vertically – mimicking a frown.

Another example comes from everyday life experiences. Think about how often people use phrases like “putting on a brave face” or “grin and bear it”. These idioms reflect an intuitive understanding of how altering one’s facial expression can impact their emotional state.

In conclusion, there is solid evidence supporting the link between facial feedback and mood. By consciously manipulating our facial expressions towards positivity (even if initially artificial), we can influence and uplift our overall emotional well-being. So next time you’re feeling down, try putting on a smile and see how it affects your mood.

Empirical Evidence Supporting the Facial Feedback Hypothesis

Let’s delve into the empirical evidence that supports the Facial Feedback Hypothesis. Numerous studies have been conducted to explore the relationship between facial expressions and emotions, providing compelling support for this intriguing theory. Here are a few examples:

• The Pen-in-Mouth Experiment: In one classic study, participants were instructed to hold a pen either between their teeth (activating smiling muscles) or between their lips (preventing smiling muscles from engaging). The results showed that those who held the pen in their teeth reported feeling happier than those with the pen in their lips. This suggests that even mimicking a smile can influence our emotional state.
• Botox and Emotional Experience: Another line of research involves studying individuals who have received Botox injections, which temporarily paralyze certain facial muscles and limit their ability to express emotions fully. Studies have found that these individuals report experiencing less intense negative emotions compared to those without Botox treatments, supporting the idea that facial expressions play a role in how we experience emotions.
• Mirror Neurons and Emotional Contagion: Mirror neurons are brain cells that fire both when we perform an action and when we observe someone else performing the same action. They contribute to our ability to empathize with others’ emotions by mirroring their facial expressions internally. Research has shown that mirroring others’ expressions can activate corresponding emotional states within ourselves, further strengthening the link between facial feedback and emotional experience.
• Cultural Universality of Facial Expressions: Cross-cultural studies examining facial expressions of emotion have consistently revealed remarkable similarities across different cultures worldwide. This suggests that certain universal patterns of facial expression are innate rather than learned behaviors, reinforcing the notion that our faces play a fundamental role in communicating and experiencing emotions.
• Neuroimaging Studies: Advanced brain imaging techniques such as functional magnetic resonance imaging (fMRI) have provided valuable insights into how our brains process emotions. These studies have shown that when we observe facial expressions, specific regions of the brain associated with emotional processing and empathy are activated, further supporting the connection between facial feedback and emotion regulation.

The empirical evidence in support of the Facial Feedback Hypothesis is both diverse and compelling. From experimental manipulations to neuroimaging studies, these findings consistently suggest that our facial expressions not only reflect our emotions but also influence how we feel. This research opens up exciting possibilities for understanding and harnessing the power of our faces to enhance emotional well-being.

Critiques and Controversies Surrounding the Hypothesis

Now let’s delve into some of the critiques and controversies surrounding the facial feedback hypothesis. While this theory has gained significant attention and support, it is not without its fair share of skepticism and debate. Let’s explore a few key examples:

• Lack of Consistency in Research Findings: One major criticism revolves around the inconsistency in research findings related to the facial feedback hypothesis. Some studies have provided evidence supporting the idea that facial expressions can influence emotions, while others have failed to replicate these results. This discrepancy has led some researchers to question the reliability and validity of the hypothesis.
• Methodological Limitations: Another point of contention lies in the methodological limitations associated with studying facial expressions and their impact on emotions. Conducting experiments in this field can be challenging due to factors such as subjective interpretation, participant biases, and difficulty controlling all variables involved. These limitations raise concerns about whether existing research truly captures a comprehensive understanding of how facial expressions influence emotional experiences.
• Alternative Explanations: Critics also propose alternative explanations for why certain studies have shown effects consistent with the facial feedback hypothesis. For instance, they argue that changes in emotional states observed during experiments could be attributed to other factors unrelated to specific muscle movements or facial expressions. These alternative explanations highlight the need for further investigation before drawing definitive conclusions about how much influence our facial muscles truly have on our emotions.
• Cultural Differences: Another aspect worth considering is cultural variation in interpreting and expressing emotions through facial expressions. What may be perceived as a universal response in one culture might differ significantly across different societies or regions. This cultural variability raises questions about whether findings from studies conducted within specific cultural contexts can be generalized to a global population.
• Publication Bias: Finally, critics draw attention to publication bias within academic journals, which tends to favor positive results over null findings or contradictory evidence regarding theories like the facial feedback hypothesis. This bias can create an inflated perception of support for the hypothesis and hinder a more balanced evaluation of its validity.

It’s important to acknowledge these critiques and controversies surrounding the facial feedback hypothesis as they shed light on potential limitations and areas for further exploration. By critically examining the existing research, we can continue to refine our understanding of how facial expressions may or may not influence our emotional experiences.

Implications for Emotional Regulation and Well-being

When it comes to emotional regulation and overall well-being, the facial feedback hypothesis offers intriguing implications. By understanding how our facial expressions can influence our emotions, we gain valuable insights into managing and improving our mental state.

Enhancing Positive Emotions:

Research suggests that deliberately adopting positive facial expressions can actually enhance our experience of positive emotions. For instance, by smiling even when we don’t feel particularly happy, we may trick our brain into thinking that we are indeed happy. This simple act of “putting on a smile” can have a profound impact on boosting mood and promoting feelings of joy and contentment.

Managing Negative Emotions:

On the flip side, the facial feedback hypothesis also sheds light on how regulating our facial expressions can help manage negative emotions. When faced with distressing situations or stressors, consciously relaxing the muscles in our face or adopting a neutral expression can help reduce intensities of anger, sadness, or anxiety. By controlling our facial expressions, we may be able to exert some control over the intensity and duration of negative emotional states.

Improving Self-awareness:

Paying attention to our own facial expressions can serve as a powerful tool for self-reflection and self-awareness. By becoming more attuned to how certain expressions correspond to specific emotions within ourselves, we become better equipped at recognizing and understanding our own emotional states. This heightened awareness allows us to respond more effectively to challenging situations by employing strategies tailored to regulate those emotions.

Strengthening Social Connections:

Our facial expressions play a vital role in social interactions as well. The ability to accurately interpret others’ emotions based on their facial cues is crucial for effective communication and building strong relationships. Understanding the link between facial expressions and emotions enables us not only to decipher others’ feelings but also empowers us with the knowledge of how our own expressions may impact those around us positively or negatively.

In conclusion, the implications of the facial feedback hypothesis for emotional regulation and well-being are vast. By recognizing the power of our facial expressions and leveraging them consciously, we can enhance positive emotions, manage negative emotions, improve self-awareness, and strengthen social connections. Incorporating this knowledge into our daily lives may lead to greater emotional balance and overall well-being.

Applications in Psychology and Therapy

One of the fascinating aspects of the facial feedback hypothesis is its potential applications in psychology and therapy. This theory suggests that our facial expressions not only reflect our emotions but also have the power to influence them. By understanding and harnessing this connection, professionals in the field can explore various ways to improve mental well-being and enhance therapeutic interventions.

Here are a few examples showcasing how the facial feedback hypothesis has been applied in psychology and therapy:

• Emotion Regulation: The ability to regulate emotions is crucial for psychological well-being. Research has shown that intentionally altering one’s facial expressions can impact emotional experiences. For instance, adopting a smiling expression, even when feeling down, may help elevate mood levels. Therapists can incorporate techniques such as “smile therapy” or encouraging clients to engage in activities that naturally elicit positive expressions to aid in emotion regulation.
• Cognitive Behavioral Therapy (CBT): CBT focuses on challenging negative thought patterns and replacing them with more positive ones. Facial feedback techniques can be integrated into CBT sessions by encouraging clients to use their facial muscles deliberately to express positive emotions during challenging situations. This practice aims to reinforce adaptive cognitive processes by aligning facial cues with desired emotional states.
• Nonverbal Communication: Facial expressions play a vital role in nonverbal communication, conveying information about one’s thoughts and feelings without words. Therapists can utilize this aspect by closely observing clients’ facial expressions during sessions, looking for signs of discomfort, tension, or hidden emotions that may provide valuable insights into their psychological state.
• Body-Mind Connection: The mind-body connection is a fundamental concept within psychology and therapy. The facial feedback hypothesis strengthens this relationship by highlighting how changes in our physical body (specifically through facial muscles) can impact our mental state. By incorporating exercises like relaxation techniques involving specific facial muscle groups, therapists aim to promote overall relaxation and reduce stress levels.
• Social Anxiety Treatment: Social anxiety disorder is characterized by intense fear of social situations. Studies have shown that individuals with social anxiety often exhibit facial expressions associated with negative emotions, such as fear or disgust, even in neutral or positive contexts. Therapists can employ techniques to help clients consciously modify their facial expressions, encouraging more relaxed and open postures to reduce anxiety and improve social interactions.

These examples illustrate the various ways in which the facial feedback hypothesis has found practical applications within the field of psychology and therapy. By exploring the influence of facial expressions on emotional experiences, professionals can develop innovative interventions to support individuals in improving their mental well-being and fostering healthier emotional responses.

Based on the research and evidence presented in this article, it is clear that the facial feedback hypothesis offers valuable insights into the connection between facial expressions and emotional experiences. By examining how our facial muscles influence our emotions, researchers have shed light on the complex interplay between our bodies and minds.

Here are a few key examples that highlight the significance of the facial feedback hypothesis:

• Facial Expressions and Emotional States: The studies discussed throughout this article consistently demonstrate a strong correlation between specific facial expressions and corresponding emotional states. For instance, when individuals were asked to hold a pen with their teeth (mimicking a smile), they reported feeling happier compared to those who held it with their lips (mimicking a frown). These findings provide compelling evidence for the impact of facial muscle activity on emotional experiences.
• Mirror Neurons and Empathy: Research has shown that observing someone else’s facial expression can activate mirror neurons in our brains, leading to an empathetic response. This suggests that not only do our own emotions influence our facial expressions, but also that witnessing others’ expressions can elicit similar emotional responses within ourselves. Such findings support the notion that facial feedback plays a crucial role in social interactions and empathy.
• Therapeutic Applications: The understanding of how facial expressions affect emotions has practical implications in various therapeutic settings. Techniques such as cognitive reappraisal, where individuals consciously alter their interpretations of situations to regulate emotions, often involve modifying one’s facial expression as well. Additionally, therapies like laughter yoga utilize forced laughter as an intervention to induce positive emotions through changes in facial muscle activity.

In conclusion, the research surrounding the facial feedback hypothesis provides compelling evidence for the bidirectional relationship between our faces and emotions. Understanding this connection can have far-reaching implications for fields such as psychology, neuroscience, and even therapy techniques aimed at enhancing well-being. As we continue to explore this fascinating area of study, further insights into how our facial expressions shape our emotional experiences are likely to emerge.

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On This Page:

The James-Lange theory of emotion states that emotions arise as a result of physiological arousal. When we encounter a stimulus, it creates a bodily response, and our brain interprets this physical reaction as an emotion. So we do not tremble because we are afraid, we are afraid because we tremble. The physical response comes before the conscious experience of emotion.

Key Takeaways

• William James (1884) and Carl Lange (1885) devised two physiological theories of emotion independently. These theories had different emphases, and some scholars argue that the James-Lange theory of emotion is a distortion of both scientists’ work.
• James-Lange theory of emotion (the 1880s) proposed that bodily changes come first and form the basis of an emotional experience. Thus, emotions are caused by bodily sensations (you become happier when you smile. You are afraid because you run).
• The James-Lange theory of emotion has spurned over a century of research into the physiology of emotion, and notable critics of the James-Lange theory (such as the Cannon-Bard theory of emotion) have also garnered tremendous traction from researchers.
• This theory has been criticized as it cannot explain emotion without any arousal nor the role of learning and cognition. It is also difficult to perceive different physiological states accurately (e.g., blood pressure).

Overview and History

William James (1948) and Carl Lange (1885) devised two distinct theories surrounding physiology and emotions independently.

While James emphasized the various somatic and visceral responses to stimuli that can prompt conscious emotional experiences, Lange had a specific emphasis. To Lange, emotion was a cardiovascular event (Lang, 1994).

Nonetheless, both scientists agreed that emotion did not begin with the conscious experience of emotion but with bodily responses to external events.

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).

William James’ original theory was constructionist, which means that James believed that there was no “essence” of any given equation; however, there were certain physiological states that organisms shared in response to stimuli (Meiselman, 2016).

Rather than attempting to categorize the plethora of individual emotions, James believed that the object of psychology was “a science of relations of mind and brain” and that it “must show how the elementary ingredients of the former correspond to the elementary functions of the latter” (1920).

The James-Lange theory of emotion owes its existence to philosophical psychology. From the last decades of the 19th century sprung a field whose quiddity was studying people’s conscious experiences.

Philosophical psychologists tended to see emotions as either primary and unanalyzable (one psychologist who believed this was Wilhelm Wundt (1896) or raw data to be examined (Lang, 1994).

William James took the latter approach and proposed that emotions were not the fundamental givens of human consciousness but phenomena prompted by the perception of somatic and visceral changes elicited by external stimuli (Lang, 1994).

Scholars have long studied the physiology of emotion prior to James (1884) and Lange (1885). Prior to the publication of James’ article in Mind , physiologists had established an empirical, lab-based science of emotions, beginning with a series of European physiologists in the 1860s (Dror, 2013).

The major figure in the study of the physiology of emotions contemporary to James was the Italian physiologist Angelo Mosso, who established the beginnings of how modern physiologists study emotion (Mosso, 1879).

Mosso framed his study of emotion in terms of the Darwinian theory of evolution and created, measured, and replicated emotions in provided graphic and numeric representations of emotional states.

James knew Mosso’s findings well and indeed acknowledged how Mosso expanded the study of emotions to the so-called viscera — the brain and its internal processes.

Mosso’s experiments and instruments would, in turn, heavily influence numerous other psychologists who studied emotions in the late 19th and early 20th centuries, such as the German physiologist Lehman, in Die Hauptgesetze des menschlichen Gefühlslebens (1892).

How Does the James-Lange Theory Work?

The James-Lange theory of emotion postulates that emotions occur as a result of physical responses to events (physiological responses to stimuli directly cause subjective feelings).

Our natural way of thinking about these standard emotions is that the mental perception of some fact excites the mental affection called the emotion and that this latter state of mind gives rise to bodily expression.

My thesis on the contrary is that the bodily changes follow directly the Perception of the exciting fact, and that our feeling of the same changes as they occur IS the emotion. Common sense says, we lose our fortune, are sorry, and weep; we meet a bear, are frightened and run; we are insulted by a rival, are angry and strike. The hypothesis here to be defended says that this order of sequence is incorrect, that the one mental state is not immediately induced by the other, that the bodily manifestation must first be interposed between, and that the more rational statement is that we feel sorry because we cry, angry because we strike, afraid because we tremble, and not that we cry, strike, or tremble because we are sorry, angry, or fearful as the case may be. Without the bodily states following on the perception the latter would be purely cognitive in form, pale, colorless, destitute of emotional warmth. We might then see the bear and judge it best to run, receive the insult and deem it right to strike, but we would not actually feel afraid or angry. James (1884)

James and Lange’s (1948; 1885) theories of emotion counter the classical idea of emotional processing, where someone imagines or experiences an emotion-eliciting event or stimulus, experiences an emotion, and then experiences a bodily reaction to that emotion (Meiselman, 2016).

Rather, the James-Lange theory of emotion argues that emotions occur due to physiological reactions to events.

To illustrate this theory, consider a person who encounters an angry, barking dog.

According to the classical theory of emotional processing, the person would hear and see the dog bark, experience an emotion (such as fear), and then experience an emotional response (such as trembling) as a result. The person trembles because they are afraid.

In contrast, according to the James-Lange theory of emotion, the person would hear the dog and tremble. Consciously, they would process this trembling and come to the conclusion because they are afraid.

The person, in this case, is afraid because they are trembling. In James’ words, “My theory…is that the bodily changes follow directly the perception of the exciting fact, and that our feeling of the same changes as they occur is the emotion” (James, 1948).

James believed that there was a set of standard emotions (for example, surprise, fear, and anger) but did not specify what may happen for emotions that do not have a distinct set of bodily reactions, such as shame (Meiselman, 2016).

Scholars have labeled the James-Lange theory of emotion as peripheralist (Meiselman, 2016) and have used the label of peripheralism to contrast the James-Lange theory of emotion with the rival Cannon-Bard theory of emotion.

In short, peripheralism is the view that emphasizes events at the periphery of an organism’s own body – such as, say, its skeletal muscles and sex organs, over events originating in the central nervous system.

Impact of the James-Lange Theory

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).

Cannon-Bard theory of Emotion

Cannon-Bard theory of emotion (1927) states that changes in emotional state and changes in the autonomic nervous system occur simultaneously but independently, both caused by the arrival of the same sensory input at the thalamus.

Cannon-Bard’s “centralist” theory of emotion emphasizes how emotions affect, firstly, the brain and nervous system. The Cannon-Bard theory of emotion assumes that stimuli elicit physiological and “affective” conscious emotional responses simultaneously.

Cannon-Bard (1925) proposed their theory of emotion as a direct response to the previously predominant James-Lange theory of emotion.

In the article, The James-Lange Theory of Emotions: A Critical Examination and An Alternative Theory (1927), Cannon offers five main criticisms of James-Lange:

• total separation of the viscera from the central nervous system does not alter emotional behavior;
• the same visceral changes occur in very different emotional states and in non-emotional states;
• the viscera are relatively insensitive structures;
• visceral changes are too slow to be a source of emotional feeling; and finally,
• artificial induction of the visceral changes typical of strong emotions does not produce them.

The James-Lange/Cannon-Bard debate is a classical one in understanding emotional processing, and numerous scholars have compared the merits of each theory in relation to others. Namely, academics have provoked a large amount of empirical research regarding the temporal sequence of emotion (emotional measurement).

For example, Allport and Tomkins (1962) bolstered the James-Lange theory of emotion by creating the facial feedback hypothesis. Rooted in the conjectures of Charles Darwin and William James , the facial feedback hypothesis puts forth that one’s facial expressions directly affect one’s emotional experience.

For example, by forcing someone’s face to contract into a smile, someone may be more likely to experience joy. A lack of facial expression, meanwhile, would result in a suppression of emotion. Nonetheless, both theories were influenced by and went on to influence others.

To illustrate this theory in the context of the dog example, a person may see a barking dog and tremble and consciously register “I am afraid” at the same time.

The person is not afraid because they are trembling, but because their thalamus has been triggered by the stimulus of an angry dog.

This means that, in a scenario where somehow someone’s physiological responses to emotion were disabled, the person would still feel the emotion of fear.

Conversely, in a situation away from the stimulus where all of the physiological responses were triggered — for example, if the parts of the brain associated with trembling were activated by the stimulation of an electrode in the absence of a frightening stimulus – the person or organism would not consciously feel fear, according to the Cannon-Bard theory of emotion.

To clarify the James-Lange theory of emotion, consider someone who experiences road rage while driving a car. Say that this person has just been cut off by a nearby car. This event is an external stimulus.

In response to being cut off, the person’s heart may race, their face may flush, their jaw may clench, and their hands may shake.

The James-Lange theory of emotion would argue that these physiological reactions are characteristic of anger.

Thus, the person experiencing these symptoms may feel angry as a direct response to these reactions and behave accordingly.

The James-Lange theory of emotion would also argue that if someone had these physiological reactions without a stimulus — say, if a machine somehow could raise their heart rate and clench their jaw — then the person would still register the emotion of anger.

James-Lange and Schacter and Singer’s Two-Factor Theory of Emotion

The James-Lange vs. Cannon-Bard debate has influenced major findings in emotion research. Some sources argue that both theories of emotion garnered a great amount of influence in early emotional physiology because of their testability (Meiselman, 2016).

Two of the most notable findings, Schachter and Singer’s two-factor theory of emotion (1962) and Damsio’s theory of emotion, draw heavily on Jamesian concepts.

The two-factor theory of emotion focuses on the interaction between emotional arousal and how organisms label that arousal. In particular, the theory argues that emotion arises from both the physiological arousal resulting from a stimulus and the reasoning that surrounds that emotion.

To use the previous example, a person may see an angry, barking dog and begin to tremble. That person then needs to consciously appraise their physiological response to the angry dog in order to determine that they are afraid.

The point of differentiation between the James-Lange and two-factor theories of emotion is subtle and lies in this cognitive appraisal. While the James-Lange theory proposes that emotion happens because of physiological arousal, the two-factor theory of emotion contends that there is a conscious appraisal of that physiological response that leads to the emotion.

For example, according to the James-Lange theory of emotion, an afraid person may say, “I am afraid because I am trembling,” that same person would say, “I am afraid because I have consciously assessed that I am trembling, and this is a response to fear.”

In other words, both the physiological response to an assessment of that response contribute to the experience of emotion, according to Schacter and Singer’s theory, and both physiological arousal and cognition need to work together in order for someone to perceive emotion.

James-Lange and Damasio’s neo-Jamesian Theory of Emotion

Damasio (1994) devised the second major theory of emotion influenced by James-Lange. Damasio proposed “somatic markers,” which are physiological reactions tied to past emotional events.

New events trigger these somatic markers and influence how people make decisions. For example, someone who has had past positive experiences with dogs (for example, a dog cuddling and protecting a person) would have a series of markers that would influence that person to, say, pet the next dog that they see.

The most notable testing of the concept of somatic markers has been the Iowa gambling task. The Iowa gambling task is a way of studying decision-making using cards. In these experiments, notably Bechara, Damasio, Damasio, and Anderson (1994), participants can choose one of four card decks and win or lose money.

Two sets of decks were “high risk” (with the possibility of losing or gaining large amounts of money), while the others were lower risk.

Bechara et al.’s original study on patients with damage to the prefrontal cortex postulated that those with brain damage were less sensitive to the consequences of their decision-making due to the “somatic marker” of brain damage.

Facial Feedback Hypothesis

The facial feedback hypothesis stems from the underlying principles of the James-Lange theory of emotion in the belief that physiological responses to stimuli generate emotion.

In the words of facial feedback researcher Tomkins (1962), emotions are “sets of muscle and glandular responses located in the face.”

Scientists have extended this facial feedback hypothesis to posture (Stepper and Strack, 1993) and, more recently, have conducted studies using Botox to fix facial expressions.

In one such study, Hennenlotter (2007) asked participants to perform a facial expression imitation task before and after being injected with Botox, which paralyzes and restricts the movement of facial muscles.

The researchers found that those who had been injected with Botox experienced less activation of brain regions associated with emotional processing when asked to imitate angry facial expressions.

Unable to imitate negative facial expressions, Hennenlotter et al. postulated that Botox injections would lead to fewer negative emotions and that the drug could be used to treat symptoms of depression.

Further studies have supported the facial feedback hypothesis.

For example, there has been evidence that smiling while reading cartoons correlates with greater levels of amusement (Hennenlotter, 2007) and that those with facial paralysis are more likely to experience depression (Hennenlotter, 2007).

This hypothesis was tested by Hennenlotter, who used Botox to treat ten patients with depression by means of suppressing muscles associated with frowning. Negative effects decreased in all patients, with nine no longer experiencing depressive symptoms.

Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1-3), 7-15.

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

Cannon, W. B. (1915). Bodily Changes in Pain, Hunger, Fear and Rage . Ed. Appleton & Company.

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.

Darwin, C., & Wundt, W. Emotion Psychologische Erklärungsmodelle.

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

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.

Hennenlotter, A., Dresel, C., Ceballos-Baumann, A., Wohlschläger, A., Castrop, F., & Haslinger, B. (2007). Denervation of frown muscles with botulinum toxin disrupts facial feedback to central circuitry of emotion. Aktuelle Neurologie, 34 (S 2), P408.

James, W. (1920). Collected essays and reviews: Longmans, Green and Company.

James, W. (1890). The principles of psychology (Vol. 1) . New York, NY: Henry Holt. Find this resource.

James, W. (1894). The physical basis of emotion. Psychological Review, 1, 516-529.

James, W. (1884). What is an emotion? Mind , 19, 188-205. Republished in K. Dunlap (Ed.), The emotions. Baltimore: Williams & Wilkins.

James, W. (1922). The emotions. Chap. XXV in Principles of Psychology , 1890. Republished in K. Dunlay (Ed.), The Emotions. Baltimore: Williams & Wilkins.

Lange, C. (1922). The emotions. In K. Dunlap (Ed.), The emotions (I. A. Haupt, Trans.; pp. 33-90). Baltimore: Williams & Wilkins. (Original work published 1885)

Lang, P. J. (1994). The varieties of emotional experience: a meditation on James-Lange theory. Psychological Review, 101 (2), 211.

Lange, C. G. (1885). The mechanism of the emotions. The Classical Psychologists , 672-684.

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

Schachter, S., & Singer, J. (1962). Cognitive, social, and physiological determinants of emotional state. Psychological Review, 69 (5), 379.

Stepper, S., & Strack, F. (1993). Proprioceptive determinants of emotional and nonemotional feelings. Journal of Personality and Social Psychology, 64 (2), 211.

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

Wundt, W. (1896). Grundriss der psychologic (C. H. Judd, Trans., 1897). Leipzig, Germany: Engelmann.

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.
• 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.
• Laird, J. D., & Lacasse, K. (2014). Bodily influences on emotional feelings: Accumulating evidence and extensions of William James’s theory of emotion. Emotion Review, 6(1), 27-34.

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• Published: 20 October 2022

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

• Nicholas A. Coles   ORCID: orcid.org/0000-0001-8583-5610 1 ,
• David S. March   ORCID: orcid.org/0000-0002-9874-7967 2 ,
• Fernando Marmolejo-Ramos   ORCID: orcid.org/0000-0003-4680-1287 3 ,
• Jeff T. Larsen 4 ,
• Nwadiogo C. Arinze   ORCID: orcid.org/0000-0002-2531-6250 5 ,
• Izuchukwu L. G. Ndukaihe   ORCID: orcid.org/0000-0003-3714-6946 5 ,
• Megan L. Willis   ORCID: orcid.org/0000-0002-2310-0018 6 ,
• Francesco Foroni   ORCID: orcid.org/0000-0002-4702-3678 6 ,
• Niv Reggev   ORCID: orcid.org/0000-0002-5734-7457 7 , 8 ,
• Aviv Mokady   ORCID: orcid.org/0000-0003-4475-0332 7 ,
• Patrick S. Forscher   ORCID: orcid.org/0000-0002-7763-3565 9 ,
• John F. Hunter   ORCID: orcid.org/0000-0001-9119-2674 10 ,
• Gwenaël Kaminski   ORCID: orcid.org/0000-0001-5300-5655 11 ,
• Elif Yüvrük   ORCID: orcid.org/0000-0001-7150-4060 12 ,
• Aycan Kapucu 12 ,
• Tamás Nagy   ORCID: orcid.org/0000-0001-5244-0356 13 ,
• Nandor Hajdu 13 ,
• Julian Tejada   ORCID: orcid.org/0000-0003-0275-3578 14 ,
• Raquel M. K. Freitag   ORCID: orcid.org/0000-0002-4972-4320 15 ,
• Danilo Zambrano   ORCID: orcid.org/0000-0003-1527-6088 16 ,
• Bidisha Som   ORCID: orcid.org/0000-0003-1942-1828 17 ,
• Balazs Aczel   ORCID: orcid.org/0000-0001-9364-4988 13 ,
• Krystian Barzykowski   ORCID: orcid.org/0000-0003-4016-3966 18 ,
• Sylwia Adamus   ORCID: orcid.org/0000-0002-7399-8735 18 ,
• Katarzyna Filip   ORCID: orcid.org/0000-0002-6181-0731 18 ,
• Yuki Yamada   ORCID: orcid.org/0000-0003-1431-568X 19 ,
• Ayumi Ikeda   ORCID: orcid.org/0000-0002-1688-2875 20 ,
• Daniel L. Eaves   ORCID: orcid.org/0000-0003-2436-7694 21 , 22 ,
• Carmel A. Levitan   ORCID: orcid.org/0000-0001-5403-444X 23 ,
• Sydney Leiweke 23 ,
• Michal Parzuchowski   ORCID: orcid.org/0000-0002-8960-0277 24 ,
• Natalie Butcher   ORCID: orcid.org/0000-0002-0154-0530 25 ,
• Gerit Pfuhl   ORCID: orcid.org/0000-0002-3271-6447 26 ,
• Dana M. Basnight-Brown   ORCID: orcid.org/0000-0002-7200-6976 27 ,
• José A. Hinojosa   ORCID: orcid.org/0000-0002-7482-9503 28 , 29 ,
• Pedro R. Montoro   ORCID: orcid.org/0000-0002-5665-8587 30 ,
• Lady G. Javela D   ORCID: orcid.org/0000-0002-9202-4354 31 ,
• Kevin Vezirian 32 ,
• Hans IJzerman   ORCID: orcid.org/0000-0002-0990-2276 32 , 33 ,
• Natalia Trujillo   ORCID: orcid.org/0000-0001-7507-1856 34 ,
• Sarah D. Pressman 35 ,
• Pascal M. Gygax   ORCID: orcid.org/0000-0003-4151-8255 36 ,
• Asil A. Özdoğru   ORCID: orcid.org/0000-0002-4273-9394 37 ,
• Susana Ruiz-Fernandez   ORCID: orcid.org/0000-0002-1709-1506 38 , 39 ,
• Phoebe C. Ellsworth   ORCID: orcid.org/0000-0002-8973-4232 40 ,
• Lowell Gaertner 4 ,
• Fritz Strack 41 ,
• Marco Marozzi   ORCID: orcid.org/0000-0001-9538-0955 42 &
• Marco Tullio Liuzza   ORCID: orcid.org/0000-0001-6708-1253 43  

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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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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.

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.

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).

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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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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What Is The Facial Feedback Hypothesis And Does It Work?

Emotions are a basic part of the human experience, and can be communicated in a number of ways. Facial expressions , however, are among the most primal, often occurring even without conscious effort. The facial feedback hypothesis is an intriguing concept suggesting that facial expressions can not only communicate emotions but can also influence our feelings.

Here, we’ll explore the facial feedback hypothesis, delve into some research about facial expressions, and answer some common questions about this fascinating hypothesis.

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. Charles Darwin studied the way animals used facial expressions and suggested the idea of facial feedback in the 1870s. In 1982, William James presented the idea that awareness of your bodily experiences is the basis of emotion. 

Through the latter half of the 1900s, the topic of facial feedback became popular again. Since then, many different studies have tested 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 instinctively 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 and 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.”

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. 

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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

Facial Feedback Hypothesis: An Overview

The facial feedback hypothesis is a widely accepted theory that proposes facial expressions can influence a person’s emotional state. In other words, facial expressions can both reflect and influence one’s emotional experience (Weiner, 2016). This hypothesis was first introduced by Charles Darwin in the late 1800s (Fridlund, 1994) and has since been the subject of numerous studies in the fields of psychology and neuroscience.

The facial feedback hypothesis proposes that facial expressions are both a result of and a contributing factor to emotional experiences. In other words, facial expressions can both reflect and influence a person’s emotional state. For example, when a person smiles, it can both reflect and contribute to an emotional state of happiness. Similarly, when a person frowns, this facial expression can both reflect and contribute to an emotional state of sadness (Weiner, 2016).

The facial feedback hypothesis has been supported by a number of studies in the fields of psychology and neuroscience. For example, a study by Strack, Martin, and Stepper (1988) found that participants who were asked to hold a pen in their teeth, which induced a smile-like expression, reported a greater sense of happiness than those who were asked to hold the pen in their lips, which induced a frown-like expression. This suggests that the facial expression induced by the pen in the participants’ mouths had an effect on their emotional state.

Similarly, a study by Dimberg, Thunberg, and Elmehed (2000) found that when participants were exposed to happy and sad facial expressions, they had similar facial responses, including changes in facial muscle activity. This suggests that the facial expressions of others can influence our own facial expressions and emotional state.

In addition, a number of neuroimaging studies have found evidence to support the facial feedback hypothesis. For example, a study by Cacioppo, Berntson, and Nouriani (1992) found that when participants were exposed to facial expressions, there was activation in the orbitofrontal cortex of the brain, which is involved in the processing of emotional information. This suggests that facial expressions can influence our emotional process.

Overall, the facial feedback hypothesis is a widely accepted theory that proposes facial expressions can influence a person’s emotional state. This hypothesis has been supported by a number of studies in the fields of psychology and neuroscience, which suggests that facial expressions can both reflect and influence our emotional experiences.

Cacioppo, J. T., Berntson, G. G., & Nouriani, B. (1992). Electrophysiological evidence of the facial feedback hypothesis. Journal of Personality and Social Psychology, 63(5), 863-876.

Dimberg, U., Thunberg, M., & Elmehed, K. (2000). Unconscious facial reactions to emotional facial expressions. Psychological Science, 11(1), 86-89.

Fridlund, A. J. (1994). Human facial expression: An evolutionary view. San Diego, CA: Academic Press.

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(5), 768-777.

Weiner, S. S. (2016). The facial feedback hypothesis: Evidence and implications. Advances in Cognitive Psychology, 12(3), 163-177.

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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).

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.

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.

Ann Senghas, Barnard College of Columbia University.

Kevin N. Ochsner, Columbia University.

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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

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When we’re happy, we smile. The corners of our mouths move out and up, our cheeks lift, and the skin around our eyes crinkles. But does it work the other way? Can posing our muscles in a smile brighten our mood?

According to an international collaboration of researchers, posing a smile can brighten our mood. (Image credit: Getty Images)

This question has been part of a long-standing debate among psychology researchers about whether facial expressions influence our emotional experience, an idea known as the facial feedback hypothesis. In a recent paper published in Nature Human Behavior , an international collaboration of researchers led by Stanford research scientist Nicholas Coles found strong evidence that posed smiles can, in fact, make us happier.

The effect isn’t strong enough to overcome something like depression, said Coles, but it provides useful insight into what emotions are and where they come from.

“We experience emotion so often that we forget to marvel at just how incredible this ability is. But without emotion, there’s no pain or pleasure, no suffering or bliss, and no tragedy and glory in the human condition,” he added. “This research tells us something fundamentally important about how this emotional experience works.”

Psychologists still aren’t sure about the origins of this central part of the human condition. One theory is that our conscious experience of emotions is based off sensations in the body – the idea that the feeling of a rapid heartbeat provides some of the sensation we describe as fear, for example. Facial feedback has often been cited as evidence for this theory, but some recent experiments have called it into question.

Before completing this project, Coles considered himself a fence-sitter on the issue. There had been seminal facial feedback research suggesting that participants found Gary Larson’s The Far Side comics funnier when they held a pen or pencil in their teeth without letting their lips touch it (supposedly activating the same muscles as a smile). But in 2016, 17 different labs tried and failed to replicate these results, casting the hypothesis into doubt.

When Coles conducted a meta-analysis of previous studies on the subject in 2019, which included a variety of different methods, his results seemed to indicate there was at least some evidence supporting facial feedback. So he decided to try to settle the matter in a way that would convince both skeptics and believers. He organized the Many Smiles Collaboration, a group that included people on both sides of the issue as well as fence-sitters like Coles, and together they devised a methodology that everyone was satisfied with.

“Rather than quibble and debate over Twitter and through journal articles, which would take decades and probably not be that productive, we said, ‘Let’s just come together and design something that would please both sides,’ ” Coles said. “Let’s figure out a way that we could potentially convince proponents that the effect isn’t real, and potentially convince critics that the effect is real.”

The researchers created a plan that included three well-known techniques intended to encourage participants to activate their smile muscles. One-third of participants were directed to use the pen-in-mouth method, one-third were asked to mimic the facial expressions seen in photos of smiling actors, and the final third were given instructions to move the corners of their lips toward their ears and lift their cheeks using only the muscles in their face.

In each group, half the participants performed the task while looking at cheerful images of puppies, kittens, flowers, and fireworks, and the other half simply saw a blank screen. They also saw these same types of images (or lack thereof) while directed to use a neutral facial expression.

In order to disguise the goal of the trial, the researchers mixed in several other small physical tasks and asked participants to solve simple math problems. After each task, participants rated how happy they were feeling.

The Many Smiles Collaboration collected data from 3,878 participants from 19 countries. After analyzing their data, the researchers found a noticeable increase in happiness from participants mimicking smiling photographs or pulling their mouth toward their ears. But much like the 2016 group, they didn’t find a strong mood change in participants using the pen-in-mouth technique.

“The effect wasn’t as reliable with the pen-in-mouth condition,” Coles said. “We’re not sure why. Going into the study, we assumed that all three techniques created the correct muscular configuration for an expression of happiness. But we found some evidence that the pen-in-mouth condition may not be actually creating an expression that closely resembles smiling.”

For instance, the act of holding the pen may require some amount of teeth-clenching that isn’t usually present in a genuine smile, which could be a confounding factor. Nonetheless, the evidence from the other two techniques is clear and provides a compelling argument that human emotions are somehow linked to muscle movements or other physical sensations.

“The stretch of a smile can make people feel happy and the furrowed brow can make people feel angry; thus, the conscious experience of emotion must be at least partially based on bodily sensations,” Coles said. “Over the past few years, the science took one step back and a few steps forward. But now we’re closer than ever to understanding a fundamental part of the human condition: emotion.”

Coles is a research scientist at Stanford University, the co-director of the Stanford Big Team Science Lab , and the director of the Psychological Science Accelerator . He conducts research on emotion, cross-cultural psychology, and models of scientific collaboration.

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Nicholas Coles, Stanford University: [email protected]

The role of customer mistreatment and emotional exhaustion in the relationship between surface acting and turnover intention

• Published: 28 May 2024

Cite this article

• I-An Wang   ORCID: orcid.org/0000-0001-8733-1520 1 ,
• Szu-Yin Lin   ORCID: orcid.org/0000-0001-5083-0932 2 &
• Tsang Shuo Chuang 3  

In the hospitality industry, service provided by frontline staff is critical to business success. Therefore, the emotional performance of service personnel will become an important factor that affects service quality. This study explores the relationships among surface acting, customer mistreatment, emotional exhaustion, and turnover intention. In addition, we focused on the mediating effect of customer mistreatment and employee emotional exhaustion on employee surface acting and turnover intention. We used survey data collected from 251 participants within the hospitality industry in Taiwan. The results revealed that customer mistreatment acts as a mediator between service-employee surface acting and their turnover intention. More specifically, surface acting by service employees relates to turnover intention, initially through customer mistreatment and subsequently through emotional exhaustion. We conclude with a discussion on the theoretical and practical implications of our results and suggest potential avenues for future research.

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The dataset analyzed during the current study is available from the first author upon reasonable request.

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Wang, IA., Lin, SY. & Chuang, T. The role of customer mistreatment and emotional exhaustion in the relationship between surface acting and turnover intention. Curr Psychol (2024). https://doi.org/10.1007/s12144-024-06128-9

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DOI : https://doi.org/10.1007/s12144-024-06128-9

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