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A microexpression[1][2]is the innate result of a voluntary and an involuntary emotional response occurring simultaneously and conflicting with one another. This occurs when the amygdala (the emotion center of the brain) responds appropriately to the stimuli that the individual experiences and the individual wishes to conceal this specific emotion. This results in the individual very briefly displaying their true emotions followed by a false emotional reaction.[3] Human emotions are an unconscious bio-psycho-social reaction that derives from the amygdala and they typically last 0.5–4.0 seconds,[4] although a microexpression will typically last less than 1/2 of a second.[5] Unlike regular facial expressions it is either very difficult or virtually impossible to hide microexpression reactions. Microexpressions cannot be controlled as they happen in a fraction of a second, but it is possible to capture someone's expressions with a high speed camera and replay them at much slower speeds.[6] Microexpressions express the seven universal emotions: disgust, anger, fear, sadness, happiness, contempt, and surprise. Nevertheless, in the 1990s, Paul Ekman expanded his list of emotions, including a range of positive and negative emotions not all of which are encoded in facial muscles. These emotions are amusement, embarrassment, anxiety, guilt, pride, relief, contentment, pleasure, and shame.[7][8]
History[edit]
Microexpressions were first discovered by Haggard and Isaacs. In their 1966 study, Haggard and Isaacs outlined how they discovered these 'micromomentary' expressions while 'scanning motion picture films of psychotherapy for hours, searching for indications of non-verbal communication between therapist and patient'[9] Through a series of studies, Paul Ekman found a high agreement across members of diverse Western and Eastern literate cultures on selecting emotional labels that fit facial expressions. Expressions he found to be universal included those indicating anger, disgust, fear, happiness, sadness, and surprise. Findings on contempt are less clear, though there is at least some preliminary evidence that this emotion and its expression are universally recognized.[10] Working with his long-time friend Wallace V. Friesen, Ekman demonstrated that the findings extended to preliterate Fore tribesmen in Papua New Guinea, whose members could not have learned the meaning of expressions from exposure to media depictions of emotion.[11] Ekman and Friesen then demonstrated that certain emotions were exhibited with very specific display rules, culture-specific prescriptions about who can show which emotions to whom and when. These display rules could explain how cultural differences may conceal the universal effect of expression.[12]
In the 1960s, William S. Condon pioneered the study of interactions at the fraction-of-a-second level. In his famous research project, he scrutinized a four-and-a-half-second film segment frame by frame, where each frame represented 1/25th second. After studying this film segment for a year and a half, he discerned interactional micromovements, such as the wife moving her shoulder exactly as the husband's hands came up, which combined yielded rhythms at the micro level.[13]
Years after Condon's study, American psychologist John Gottman began video-recording living relationships to study how couples interact. By studying participants' facial expressions, Gottman was able to correlate expressions with which relationships would last and which would not.[14] Gottman's 2002 paper makes no claims to accuracy in terms of binary classification, and is instead a regression analysis of a two factor model where skin conductance levels and oral history narratives encodings are the only two statistically significant variables. Facial expressions using Ekman's encoding scheme were not statistically significant.[15] In Malcolm Gladwell's book Blink, Gottman states that there are four major emotional reactions that are destructive to a marriage: defensiveness which is described as a reaction toward a stimulus as if you were being attacked, stonewalling which is the behavior where a person refuses to communicate or cooperate with another,[16]criticism which is the practice of judging the merits and faults of a person, and contempt which is a general attitude that is a mixture of the primary emotions disgust and anger.[17] Among these four, Gottman considers contempt the most important of them all.[18]
Micro Expression Training Tool
Types[edit]
Microexpressions are typically classified based on how an expression is modified. They exist in three groups:
- Simulated expressions: when a microexpression is not accompanied by a genuine emotion. This is the most commonly studied form of microexpression because of its nature. It occurs when there is a brief flash of an expression, and then returns to a neutral state.[19]
- Neutralized expressions: when a genuine expression is suppressed and the face remains neutral. This type of micro-expression is not observable due to the successful suppression of it by a person.[19]
- Masked expressions: when a genuine expression is completely masked by a falsified expression. Masked expressions are microexpressions that are intended to be hidden, either subconsciously or consciously.[20]
In photographs and films[edit]
Microexpressions can be difficult to recognize, but still images and video can make them easier to perceive. In order to learn how to recognize the way that various emotions register across parts of the face, Ekman and Friesen recommend the study of what they call 'facial blueprint photographs,' photographic studies of 'the same person showing all the emotions' under consistent photographic conditions.[21] However, because of their extremely short duration, by definition, microexpressions can happen too quickly to capture with traditional photography. Both Condon and Gottman compiled their seminal research by intensively reviewing film footage. Frame rate manipulation also allows the viewer to distinguish distinct emotions, as well as their stages and progressions, which would otherwise be too subtle to identify. This technique is demonstrated in the short film Thought Moments by Michael Simon Toon and a film in Malayalam Pretham 2016[22][23][24]Paul Ekman also has materials he has created on his website that teach people how to identify microexpressions using various photographs, including photos he took during his research period in New Guinea.[25]
Moods vs emotions[edit]
Moods differ from emotions in that the feelings involved last over a longer period. For example, a feeling of anger lasting for just a few minutes, or even for an hour, is called an emotion. But if the person remains angry all day, or becomes angry a dozen times during that day, or is angry for days, then it is a mood.[26] Many people describe this as a person being irritable, or that the person is in an angry mood. As Paul Ekman described, it is possible but unlikely for a person in this mood to show a complete anger facial expression. More often just a trace of that angry facial expression may be held over a considerable period: a tightened jaw or tensed lower eyelid, or lip pressed against lip, or brows drawn down and together.[27]Emotions are defined as a complex pattern of changes, including physiological arousal, feelings, cognitive processes, and behavioral reactions, made in response to a situation perceived to be personally significant.[28]
Controlled microexpressions[edit]
Facial expressions are not just uncontrolled instances. Some may in fact be voluntary and others involuntary, and thus some may be truthful and others false or misleading.[29] Facial expression may be controlled or uncontrolled. Some people are born able to control their expressions (such as pathological liars), while others are trained, for example actors. 'Natural liars' may be aware of their ability to control microexpressions, and so may those who know them well; they may have been 'getting away' with things since childhood due to greater ease in fooling their parents, teachers, and friends.[30] People can simulate emotion expressions, attempting to create the impression that they feel an emotion when they are not experiencing it at all. A person may show an expression that looks like fear when in fact they feel nothing, or perhaps some other emotion.[31] Facial expressions of emotion are controlled for various reasons, whether cultural or by social conventions. For example, in the United States many little boys learn the cultural display rule, 'little men do not cry or look afraid.' There are also more personal display rules, not learned by most people within a culture, but the product of the idiosyncrasies of a particular family. A child may be taught never to look angrily at his father, or never to show sadness when disappointed. These display rules, whether cultural ones shared by most people or personal, individual ones, are usually so well-learned, and learned so early, that the control of the facial expression they dictate is done automatically without thinking or awareness.[32]
Emotional intelligence[edit]
Involuntary facial expressions can be hard to pick up and understand explicitly, and it is more of an implicit competence of the unconscious mind. Daniel Goleman created a conclusion on the capacity of an individual to recognize their own, as well as others' emotions, and to discriminate emotions based on introspection of those feelings. This is part of Goleman's emotional intelligence. In E.I, attunement is an unconscious synchrony that guides empathy. Attunement relies heavily on nonverbal communication.[33] Looping is where facial expressions can elicit involuntary behavior, In the research motor mimicry there shows neurons that pick up on facial expressions and communicate with motor neurons responsible for muscles in the face to display the same facial expression. Thus displaying a smile may elicit a micro expression of a smile on someone who is trying to remain neutral in their expression.[34]
The amygdala is the emotion center of the brain
Through fMRI we can see the area where these Mirror neurons are located lights up when you show the subject an image of a face expressing an emotion using a mirror. In the relationship of the prefrontal cortex also known as the (executive mind) which is where cognitive thinking experience and the amygdala being part of the limbic system is responsible for involuntary functions, habits, and emotions. The amygdala can hijack the pre-frontal cortex in a sympathetic response. In his book Emotional Intelligence Goleman uses the case of Jason Haffizulla (who assaulted his high school physics teacher because of a grade he received on a test) as an example of an emotional hijacking this is where rationality and better judgement can be impaired.[33] This is one example of how the bottom brain can interpret sensory memory and execute involuntary behavior. This is the purpose of microexpressions in attunement and how you can interpret the emotion that is shown in a fraction of a second. The microexpression of a concealed emotion that's displayed to an individual will elicit the same emotion in them to a degree, this process is referred to as an emotional contagion.[34] Being able to introspect these emotions can have applications to having more accurate judgements on an individuals intentions although accuracy depends a lot of factors. Accuracy can be determined by an web based microemotional aptitude test called the Profile of Nonverbal Sensitivity (PONS) which is similar to the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) which tests the ability to read emotions.
MFETT and SFETT[edit]
Micro Facial expression training tools and subtle Facial expression training tools are software made to develop someone's skills in the competence of recognizing emotion. The software consists of a set of videos that you watch after being educated on the facial expressions. After watching a short clip, there is a test of your analysis of the video with immediate feedback. This tool is to be used daily to produce improvements. Individuals that are exposed to the test for the first time usually do poor trying to assume what expression was presented, but the idea is through the reinforcement of the feedback you unconsciously generate the correct expectations of that expression. These tools are used to develop rounder social skills and a better capacity for empathy. They are also quite useful for development of social skills in people on the autism spectrum.[34] Although lie detection is not only an important skill in social situations and the workplace, but is a vital aspect to law enforcement and other occupations that deal with continual acts of deception. Microexpression and subtle expression recognition are valuable assets for these occupations as it increases the chance of detecting deception. In recent years it was found that the average person has a 54% accuracy rate in terms of exposing whether a person is lying or being truthful.[35] However, Ekman had done a research experiment and discovered that secret service agents have a 64% accuracy rate. In later years, Ekman found groups of people that are intrigued by this form of detecting deception and had accuracy rates that ranged from 68% to 73%. Their conclusion was that people with the same training on microexpression and subtle expression recognition will vary depending on their level of emotional intelligence.[35]
Lies and leakage[edit]
The sympathetic nervous system is one of two divisions under the autonomic nervous system, it functions involuntarily and one aspect of the system deals with emotional arousal in response to situations accordingly.[36] Therefore, if an individual decides to deceive someone, they will experience a stress response within because of the possible consequences if caught. A person using deception will typically cope by using nonverbal cues which take the form of bodily movements. These bodily movements occur because of the need to release the chemical buildup of cortisol, which is produced at a higher rate in a situation where there is something at stake.[37] The purpose for these involuntary nonverbal cues are to ease oneself in a stressful situation. In the midst of deceiving an individual, leakage can occur which is when nonverbal cues are exhibited and are contradictory to what the individual is conveying.[38] Despite this useful tactic of detecting deception, microexpressions do not show what intentions or thoughts the deceiver is trying to conceal. They only provide the fact that there was emotional arousal in the context of the situation. If an individual displays fear or surprise in the form of a microexpression, it does not mean that the individual is concealing information that is relevant to investigation. This is similar to how polygraphs fail to some degree: because there is a sympathetic response due to the fear of being disbelieved as innocent. The same goes for microexpressions, when there is a concealed emotion there is no information revealed on why that emotion was felt. They do not determine a lie, but are a form of detecting concealed information. David Matsumoto is a well-known American psychologist and explains that one must not conclude that someone is lying if a microexpression is detected but that there is more to the story than is being told.[39]Paul Ekman created a paradigm to determine the confidence in deception apprehension due to the context of the situation and the person to be the liar themselves. The situational factors can be the type of person, any relationships, or the type of lie they are telling, or whether it is the act of withholding information or telling a false information. If a lie is successful, it can be followed by expressions of false delight, which is when happiness expressed in the satisfaction of the deceiver, or deception guilt, which can come on as an expression of fear or sadness.
There are also behavioral signs of false expressions or when an emotional expression is not genuinely being felt. Usually these can be interpreted implicitly because they are out of sync, similar to when something feels off about what somebody says, but these sign can go unnoticed.[40]
- Fear: when there is absence of the reliable forehead expression
- Sadness: when there is absence of the reliable forehead expression
- Happiness: lack of wrinkle around the eye (eye muscles not being involved)
- Negative emotions: absence of sympathetic somatic response.
- Any emotions: asymmetrical expression, onset of expression incongruent or abrupt.
Universality[edit]
Universal Facial Expressions
A significant amount of research has been done in respect to whether basic facial expressions are universal or are culturally distinct. After Charles Darwin had written The Expression of the Emotions in Man and Animals it was widely accepted that facial expressions of emotion are universal and biologically determined.[41] Many writers have disagreed with this statement. David Matsumoto however agreed with this statement in his study of sighted and blind Olympians. Using thousands of photographs captured at the 2004 Olympic and Paralympic Games, Matsumoto compared the facial expressions of sighted and blind judo athletes, including individuals who were born blind. All competitors displayed the same expressions in response to winning and losing.[42] Matsumoto discovered that both blind and sighted competitors displayed similar facial expression, during winnings and loss. These results suggest that our ability to modify our faces to fit the social setting is not learned visually.[42]
Facial Action Coding System[edit]
The Facial Action Coding System or FACS is used to identify facial expression. This identifies the muscles that produce the facial expressions. To measure the muscle movements the action unit (AU) was developed. This system measures the relaxation or contraction of each individual muscle and assigns a unit. More than one muscle can be grouped into an Action Unit or the muscle may be divided into separate action units. The score consists of duration, intensity and asymmetry. This can be useful in identifying depression or measurement of pain in patients that are unable to express themselves.[43]
The Facial Action Coding System training manual, first published in 1978 with multimedia supplements, is designed to teach individuals how to detect and categorize facial movements. The guide provides lessons and practice for memorizing action units and combinations of action units. The manual's purpose is to enable practitioners to recognize different physiological attributes of facial expressions, but leaves the interpretation of this data up to other works. Users should not expect to become face-reading experts. It can be particularly useful to behavioral scientists, CG animators, or computer scientists when they need to know the exact movements that the face can perform, and what muscles produce them. It also has potential to be a valuable tool for psychotherapists, interviewers, and other practitioners who must penetrate deeply into interpersonal communications.[44] A new version (2002) of FACS by Paul Ekman, Wallace V. Friesen, and Joseph C. Hager is now available with several core improvements, including more accurate representations of facial behaviors and cleaner, digital images. Other related tools for facial expression recognition training include the Micro Expression Training Tool (METT) and Subtle Expression Training Tool (SETT), both developed by Paul Ekman.[43] The pioneer F-M Facial Action Coding System 3.0 (F-M FACS 3.0) [45] was created in 2018 by Dr. Freitas-Magalhães, and presents 5,000 segments in 4K, using 3D technology and automatic and real-time recognition (FaceReader 7.1). The F-M FACS 3.0 features 8 pioneering action units (AUs) and 22 pioneering tongue movements (TMs), in addition to functional and structural nomenclature.
Within the scope of its pioneering theory NeuroFACS 3.0, Dr. Freitas-Magalhães created the developed concepts of Neuromicroexpressions and Neuromacroexpressions [46][47].
In popular culture[edit]
Microexpressions and associated science are the central premise for the 2009 television series Lie to Me, based on discoveries of Paul Ekman. The main character uses his acute awareness of microexpressions and other body language clues to determine when someone is lying or hiding something.
They also play a central role in Robert Ludlum's posthumously published The Ambler Warning, in which the central character, Harrison Ambler, is an intelligence agent who is able to see them. Similarly, one of the main characters in Alastair Reynolds' science fiction novel, Absolution Gap, Aura, can easily read microexpressions.
In The Mentalist, the main character, Patrick Jane, can often tell when people are being dishonest. However, specific reference to microexpressions is only made once in the 7th and final season.
In the 2015 science fiction thriller Ex Machina, Ava, an artificially intelligent humanoid, surprises the protagonist, Caleb, in their first meeting, when she tells him 'Your microexpressions are telegraphing discomfort.'
Controversy[edit]
Though the study of microexpressions has gained popularity through popular media, studies show it lacks internal consistency[example needed] in its conceptual formation.[48]
See also[edit]
References[edit]
- ^Freitas-Magalhães, A. (2012). Microexpression and macroexpression. In V. S. Ramachandran (Ed.), Encyclopedia of Human Behavior (Vol. 2, pp. 173–183). Oxford: Elsevier/Academic Press. ISBN978-0-12-375000-6
- ^Freitas-Magalhães, A. (2019). Human Microexpressions: Brain, Face and the Emotion.Porto: FEELab Science Books. ISBN9789898766649
- ^'Empathy, emotion dysregulation, and enhanced microexpression recognition ability'. Retrieved 2018-03-20.
- ^'Background factors predicting accuracy and improvement in micro expression recognition'. Retrieved 2018-03-20.
- ^'Background factors predicting accuracy and improvement in micro expression recognition'. archive.is. 2011-07-15. Retrieved 2018-03-20.
- ^https://www.researchgate.net/publication/224160151_Facial_micro-expressions_recognition_using_high_speed_camera_and_3D-gradient_descriptor
- ^Ekman, Paul (1999). 'Basic Emotions'. In T. Dalgleish and M. Power (eds.). Handbook of Cognition and Emotion. Sussex, UK: John Wiley & Sons, Ltd.CS1 maint: uses editors parameter (link)
- ^Ekman, Paul (1992). 'Facial Expressions of Emotion: An Old Controversy and New Findings'. Philosophical Transactions of the Royal Society. London. B335 (1273): 63–69. doi:10.1098/rstb.1992.0008.
- ^Haggard, E. A., & Isaacs, K. S. (1966). Micro-momentary facial expressions as indicators of ego mechanisms in psychotherapy. In L. A. Gottschalk & A. H. Auerbach (Eds.), Methods of Research in Psychotherapy (pp. 154–165). New York: Appleton-Century-Crofts.
- ^Matsumoto, David (1992). 'More evidence for the universality of a contempt expression'. Motivation and Emotion. 16 (4). doi:10.1007/bf00992972.
- ^Ekman, P.; Friesen, W.V. (1971). 'Constants across cultures in the face and emotion'(PDF). Journal of Personality and Social Psychology. 17 (2): 124–129. doi:10.1037/h0030377. PMID5542557.
- ^Ekman, Paul (1989). H. Wagner & A Manstead (ed.). Handbook of social psychophysiology. Chichester, England: Wiley. pp. 143–164. Chapter: The argument and evidence about universals in facial expressions of emotion.
- ^http://journals.lww.com/jonmd/Citation/1966/10000/Sound_Film_Analysis_of_Normal_and_Pathological.5.aspx Sound Film Analysis of Normal and Pathological Behavior Patterns, Condon, W.S.; Ogston, W.D., Journal of Nervous & Mental Disease. 143(4):338–347, October 1966.
- ^'Research FAQs'. Gottman.com. The Gottman Institute. Retrieved 2013-10-26.
- ^Gottman, J.; Levenson, R.W. (2002). 'A Two-Factor Model for Predicting When a Couple Will Divorce: Exploratory Analyses Using 14-Year Longitudinal Data'. Family Process. 41 (1): 83–96. doi:10.1111/j.1545-5300.2002.40102000083.x. Archived from the original on 2013-01-05.Cite uses deprecated parameter
|dead-url=
(help) - ^Webber, Elizabeth; Feinsilber, Mike (1999). Merriam-Webster's Dictionary of Allusions. Merriam-Webster. pp. 519–. ISBN9780877796282. Retrieved 10 December 2012.
- ^TenHouten, W.D. (2007). General Theory of Emotions and Social Life. Routledge.
- ^Gladwell, Malcolm (2005). Blink, Chapter 1, Section 3, The Importance of Contempt
- ^ abhttp://www.cse.usf.edu/~mshreve/publications/FG11.pdf
- ^Godavarthy, Sridhar. 'Microexpression spotting in video using optical strain'. Web. Retrieved 15 June 2011.
- ^Ekman, P. & Friesen, W.V. (2003). Unmasking the Face. Cambridge: Malor Books. p. 169
- ^Prof. Ragodí. 'Trabajo Psicología de 1er Trimestre.' El Bigote de Bernays. Blogspot. Updated 11-19-2009. Accessed 8-5-13. http://elbigotedebernays.blogspot.com/2009/11/trabajo-psicologia-1er-trimestre.html
- ^Braun, Roman. 'Eye Catcher.' Trinergy-NLP-Blog. Posted 10-27-2009. Accessed 8-5-13. 'Archived copy'. Archived from the original on 2013-12-13. Retrieved 2013-08-06.Cite uses deprecated parameter
|deadurl=
(help)CS1 maint: archived copy as title (link) - ^'Thought Moments.' British Films Directory. British Council. Updated 12-1-2009.http://film.britishcouncil.org/thought-moments
- ^http://www.paulekman.com/products/
- ^Ekman, P. & Friesen, W.V. (2003). Unmasking the Face. Cambridge: Malor Books. p. 12.
- ^Ekman, P. & Friesen, W.V. (2003). Unmasking the Face. Cambridge: Malor Books. pp. 12–13.
- ^http://www.apa.org/research/action/glossary.aspx#e
- ^Ekman, P. & Friesen, W.V. (2003). Unmasking the Face. Cambridge: Malor Books. p. 19.
- ^Ekman, P. (1991). Telling Lies Clues to deceit in the Marketplace, Politics, and Marriage. New York: W.W. Norton & Company Inc., p. 56.
- ^Ekman, P. & Friesen, W.V. (2003). Unmasking the Face. Cambridge: Malor Books. p. 20.
- ^Ekman, P. & Friesen, W.V. (2003). Unmasking the Face. Cambridge: Malor Books. pp. 20–21.
- ^ abGoleman, Daniel (1995). Emotional intelligence. New York: Bantam Books.
- ^ abcGoleman, Daniel (2006). Social intelligence: the new science of human relationships. New York: Bantam Books.
- ^ ab'Detecting Deception from Emotional and Unemotional Cues'. Retrieved 2018-03-20.
- ^Boeree, George. 'The Limbic System'. webspace.ship.edu. Retrieved 2018-03-25.
- ^'Cortisol | Hormone Health Network'. www.hormone.org. Retrieved 2018-03-25.
- ^'Interpreting Nonverbal Communication for Use in Detecting Deception'. Retrieved 2018-03-25.
- ^Matsumoto, D. (2010, March 21). Dr. David Matsumoto: How to Tell a Lie with the Naked Eye. Retrieved from Spying for Lying: 'Archived copy'. Archived from the original on 2013-05-28. Retrieved 2012-11-23.Cite uses deprecated parameter
|deadurl=
(help)CS1 maint: archived copy as title (link) - ^Freitas-Magalhães, A. (2013). The Face of Lies. Porto: FEELab Science Books. ISBN978-989-98524-0-2
- ^Darwin, C. (1872). The Expression of the Emotions in Man and Animals. London: John Murray.
- ^ abBible, E. (2009, January 7). Smiles and frowns are innate, not learned. Retrieved from San Francisco State University: http://www.sfsu.edu/news/2009/spring/1.html
- ^ abhttp://www.paulekman.com/facs/
- ^'Facial Action Coding System (FACS) and the FACS Manual'. Face-and-emotion.com. Archived from the original on 2013-10-19. Retrieved 2013-10-26.Cite uses deprecated parameter
|deadurl=
(help) - ^Freitas-Magalhães, A. (2018). Facial Action Coding System 3.0: Manual of Scientific Codification of the Human Face. Porto: FEELab Science Books. ISBN978-989-8766-86-1.
- ^Freitas-Magalhães, A. (2018). Human Microexpressions: Brain, Face and the Emotion.Porto: FEELab Science Books. ISBN9789898766649
- ^Freitas-Magalhães, A. (2019). NeuroFACS 3.0: The Neuroscience of Face.Porto: FEELab Science Books. ISBN9789898766793
- ^http://pss.sagepub.com/content/19/5/508.abstract
Further reading[edit]
- Matthew Hertenstein (2015). The Tell: The Little Clues That Reveal Big Truths about Who We Are. Basic Books. ISBN978-0465036592.
External links[edit]
- Microexpressions Complicate Face Reading, by Medical News Today August 2007
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Microexpression&oldid=907991644'
Published online 2009 Jul 20. doi: 10.1186/1472-6920-9-47
PMID: 19619307
This article has been cited by other articles in PMC.
Abstract
Background
Patients provide emotional cues during consultations which may be verbal or non-verbal. Many studies focus on patient verbal cues as predictors of physicians' ability to recognize and address patient needs but this project focused on non-verbal cues in the form of facial micro-expressions. This pilot study investigated first year medical students' (n = 75) identified as being either good or poor communicators abilities to detect emotional micro-expressions before and after training using the Micro Expression Training Tool (METT) http://www.mettonline.com.
Methods
The sample consisted of 24 first year medical students, 9 were from the lowest performance quartile in a communication skills OSCE (Objective Structured Clinical Exam) station and 15 were from the highest performance quartile. These students completed the METT individually, recording pre- and post-assessment scores. Students were also invited to provide their views on the training.
Results
No difference in pre-assessment scores was found between the lowest and highest quartile groups (P = 0.797). After training, students in the high quartile showed significant improvement in the recognition of facial micro-expressions (P = 0.014). The lowest quartile students showed no improvement (P = 0.799).
Conclusion
In conclusion, this pilot study showed there was no difference between the ability of medical undergraduate students assessed as being good communicators and those assessed as poor communicators to identify facial micro-expressions. But, the study did highlight that those students demonstrating good general clinical communication benefited from the training aspect of the METT, whereas low performing students did not gain. Why this should be the case is not clear and further investigation should be carried out to determine why lowest quartile students did not benefit.
Background
Emotions, and their recognition in those we communicate with make it possible to behave flexibly in different situation as we regulate our social interactions[]. One interaction where emotions are frequently shown by participants is the doctor-patient consultation. In his article 'Emotions revealed: recognising facial expressions' Paul Ekman states that recognising facial expressions, including the less obvious facial micro-expressions of patients may be useful to a doctor in their interactions [2]. Being able to perceive facial expressions accurately may aid in interpreting how much pain a patient is experiencing. In one study which interviewed Certified Nursing Assistants in an American care home one method the nursing assistants used to gauge the pain level in cognitively impaired residents was their facial expressions[]. A further use would be to pick up clues to the patients emotional state. Archinard studied the behavioural responses of a doctor when interviewing patients who had attempted suicide[]. Encyclopedia of chess endings free download. Although the doctor appeared to pick up on facial expression cues from the patients to distinguish between those who would re-attempt suicide, as they behaved differently towards such patients; they were unable to use this information consciously to assign those patients as being at risk of re-attempting suicide. That is, although the doctor could discriminate and behave differently towards individuals who would repeatedly attempt suicide and those would not repeat, this information was not, or could not, be utilised when clinical decisions were made.
Emotional cues may be verbal or non-verbal[5]. Levinson et al found that responding to emotions expressed verbally by patients may result in shorter consultations[], but the same study found that physicians responded positively to patients' verbal emotional cues in only 38% of surgery cases and 21% of primary care cases. Similar results were noted in oncologists in response to verbal cues from cancer patients, where only 28% of emotional cues were responded to appropriately[]. Another study noted that cues were most likely to be missed by doctors if they did not directly state the emotional impact on the patient[]. If a verbal message is ambiguous non-verbal behaviour, such as facial expression may elucidate what is meant[,].
There is mounting literature to suggest that a patient-centred model of care, whereby physicians address patients' emotional concerns and biomedical conditions should be adopted[10] and that such a positive interaction between doctors and patient is important for patient outcomes[]. It is difficult to address emotional concerns if these are not recognised by doctors. Therefore the recognition of emotions in patients, using verbal or non-verbal cues is one of the important skills which can aid doctors in creating patient centred communications. Difficulties in communicating with patients have been shown in several studies to relate to complaints against doctors. For example, in a longitudinal study, Tamblyn et al. [] reported that nearly one in five physicians had a retained complaint filed with the medical authorities in the first 2 to 12 years of practice, and physicians who scored in the lowest quartile of their Clinical Skills Exam (CSE) were at significantly greater risk of complaints than those in higher quartiles. Communication was one component of the CSE that was an important predictor of future complaints to the medical authorities.
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One question this pilot study therefore wanted to ask was whether one reason for poor communication was due to an inability to recognise facial expressions. This was done by investigating whether there was a difference in the ability of medical students identified as good or poor communicators to perceive facial micro-expressions. Micro-expressions are brief (lasting up to 0.2 seconds) partial expressions which are less obvious than a full (or cardinal) facial expression[2]. The hypothesis tested was that individuals classified as good communicators would perceive facial micro-expressions more accurately than those classified as poor communicators. If this were indeed the case then this would provide us with one area that we could help such students in their clinical communication training.
Most medical schools currently incorporate an aspect of clinical communication training into their curriculum[]. Training has been shown to be effective at improving the communicatory abilities of medical students, and these benefits can persist[,]. The training can employ a variety of methods including opportunities to practice particular skills with other students, or actors portraying the role of patients[]. A 1989 paper by Lavelle[] describes a course for medical students in 'The objective methods of clinical practice' a component of which was training in the recognition of full, cardinal, emotional facial expressions. Although no data is presented the author reports that 'Students' capacity to read single emotions remains much the same, but their ability to read multiple emotions improves dramatically'. In that study the students performance in the recognition of single full emotional facial expressions was maximal prior to training, whereas the recognition of multiple expressions was not and therefore training had an impact. A further question this pilot study wanted to investigate was whether skills such as recognition of facial micro-expressions could be taught explicitly to medical students.
Both research questions will be investigated by the use of the Micro-Expression Training Tool (METT) developed by Paul Ekman http://www.mettonline.com. https://nfnhhu.weebly.com/blog/ironcad-keygen-torrent. The METT has been used previously to investigate the ability to perceive micro-expressions in a group of student participants[17] but there are currently no published studies investigating it's use in Health professionals.
Methods
Participants
Seventy-five pre-selected subjects consisting of first year medical students at the University of St. Andrews were invited to participate in this study. Pre-selection was based on the results of an OSCE (Objective Structured Clinical Exam) communications skills station half way through their first year of study, with those invited being in either the highest or lowest performance quartiles. The OSCE communication station involved talking to a simulated patient portraying a role in a General Practice context of someone who had fallen and hurt their ankle. The scoring tool contained both checklist and rating components. Checklist items included gathering information relating to the presenting complaint as well as past medical and social history. Areas where students were rated included introductions, ability to respond to patient perspective, concluding a consultation and a large proportion of the marks were available for global communication skills such as rapport/empathy, listening skills and non-verbal behaviour. Simulated patients also rated their satisfaction in the encounter. Students were recruited via an e-mail invitation to participate. Interested students were given an information sheet and a consent form.
Materials and Procedures
During the study participants individually completed pre- and post-assessment, training, practice and review sections of the Micro-Expression Training Tool (METT) http://www.mettonline.com under examination conditions. In the pre-assessment, subjects viewed fourteen flashed example faces of micro-expressions, consisting of either, disgust, sadness, happiness, contempt, fear, anger or surprise. Subjects were prompted to select one of the seven emotional labels. On completion of the pre-assessment a score, expressed as percentage correct, was assigned and recorded.
The next part of the CD ROM was a training session, where a narrator explained, in a slow-motion video clip, the four pairs of commonly confused emotions, e.g. fear/sadness, happy/contempt, surprise/fear and disgust/anger. The narrator provided explicit examples of differences and similarities in the regions of the eyes, nose and mouth. 'The eyebrows are pulled down together in both these angry expressions . . . the biggest difference between them is in the mouth. The lips are pressed tightly on the right but they're open with tense lips, probably saying something quite unpleasant on the left'. Following this was a practice session where subjects labelled 28 facial expressions, and, if incorrect, a still picture was paused for as long as necessary until the subject selected the correct emotional label. Like in the training section, the review used alternative faces to display four pairs of commonly confused expressions. The post-assessment followed the same procedure as the pre-assessment and again a score was recorded. Finally, participants were invited to provide open comments on any aspect of the METT and it's relation to their training in clinical communication.
Results were investigated for normality. All data apart from the OSCE results were normally distributed therefore the OSCE data was log transformed. Appropriate statistical tests (alpha level set to 0.05) were applied using SPSS v14.
This study was approved by the Bute Medical School Ethics Committee (MD3498).
Results
Quantitative results
Nine subjects from the lowest quartile (4 males, 5 females) and fifteen from the highest quartile (5 males, 10 females) consented to participate in the study (participation rate of 32%). The OSCE results of the students who volunteered to take part in the study were compared to the rest of the appropriate quartile cohort. There was no difference in OSCE scores between the volunteers and the rest of the cohort for either the lowest quartile (participant mean ± standard deviation = 42.19 ± 5.43, non-participant = 35.13 ± 14.82) or the highest quartile group (participant mean ± standard deviation = 81.25 ± 6.22, non-participant = 82.38 ± 4.80).
Surprisingly, there was no difference between the highest and lowest quartile students terms of METT pre-assessment scores (t = -0.261, df = 20, P = 0.797). When the difference between METT pre and post-assessment results were examined however a difference did emerge between the high and low quartile groups. No difference was found between the pre- and post-assessment score in the lowest quartile test subjects (paired t-test, t = -0.265, df = 7, P = 0.799), but there was a difference between these two scores for the highest quartile group (t = -2.580, df = 13, P = 0.014). Means and standard deviations of pre- and post-assessment scores are shown in Table Table1.1. The highest quartile students improved their ability to identify facial micro-expression after training whilst the lowest quartile students did not (Figure (Figure11).
Table 1
Mean and standard deviation of the pre- and post-assessments
Mean | Standard deviation | ||
Lowest | Pre-assessment | 67.88 | 17.88 |
Post-assessment | 69.63 | 16.19 | |
Highest | Pre-assessment | 69.50 | 11.45 |
Post-assessment | 76.36 | 11.04 |
Mean and standard deviation of the pre and post training assessment scores for both the highest and lowest quartile groups.
Average scores for pre-and post-assessments. Average scores on the pre- and post assessments of the METT for students in the lowest quartile and highest quartile groups. Error bars represent standard errors.
Qualitative comments
Students in both groups saw the relevance of the training. The following quotes were made by participants from the highest and lowest quartile groups respectively:
'I think this program was relevant and very insightful for those studying medicine. In an OSCE station this would come into use with patient-doctor consultation and history taking'
'Generally I thought this was a worthwhile study, and I particularly liked the training and the fact that it gave you the chance to recognise the actual expressions.'
They also found some aspects difficult, for example, one lowest quartile student commented:
'Some facial expressions were really hard to distinguish between, but the training really helped'.
Subtle Expression Training Tools
Students however, saw some limitations in it's application, for example this student in the lowest quartile group:
'The training program was very good but the test showed the picture too quickly, so I thought it unrealistic. Especially when in the OSCE or real life I would be getting information from tone of voice and other body language'.
Discussion
In the current study there was no difference between the abilities of students assessed as being either good or poor communicators in the METT baseline measure of perception of facial micro-expression (pre-assessment). This suggests that an inability to recognise facial expressions in patients was not the reason that these students were performing poorly in their communication skills assessments. There are various other potential reasons that communication with patients is ineffective including poor non-verbal communication behaviour from the health professional[,], or lack of appropriate verbal responses to cues from the health professional[,]. It may even be, as was suggested in the study by Archinard et al, that the facial expression information could be perceived by the health professional but not consciously acted upon[]. From this small study it is impossible to determine which areas these students were poorly performing in.
The highest quartile students showed a significant improvement in their ability to perceive facial micro-expressions after training whilst the lowest quartile students did not, therefore the METT could be used to improve performance. Why there was a difference in improvement between the two groups in the current study is not clear, although it could be due to a variety of reasons including the low quartile group; requiring a longer period of training, having greater difficulty in perceiving the differences highlighted in the training, or being poorer at learning or less motivated to improve. Anxiety, including social anxiety may also impact on attention and learning[23,24]. This study could not be used to determine which of these possible reasons is valid for these students. Understanding why the higher quartile group benefited most is important for the potential to understand which aspects of the training improved their performance but did not impact on the lower quartile group and why this was the case. This could inform targeted training for future medical students. The students generally commented that they found training interesting and viewed it as useful.
This study has several limitations. The METT involves static facial micro-expressions. This may not be directly comparable to the ability to perceive such expressions in real time interactions, indeed this point was raised by one of the students in the study (see qualitative results). There are anatomical and physiological differences in brain response when an individual is viewing dynamic facial images compared to static images[] and this may affect behavioural responses. Future work should concentrate on perception of facial expressions in video footage or real interactions.
Micro Expression Training Tool Mett Download Free
Unfortunately the participation rate was low for this pilot study. More subjects would be required to confirm this effect and explore the link between assessed communication ability and improvement in perception of micro-expressions with training. This pilot study did however show the feasibility of utilising this CD ROM for undergraduate medical student training.
When considering facial expressions alone, Ekman[] points out eight kinds to be aware of: from none to sub-visible, momentary, subtle, full, false, referential and mock. Our study was restricted to momentary facial micro-expressions, therefore the ability to perceive other types of expressions was not investigated. Previous work has shown that medical students do benefit from training in the recognition of multiple facial expressions but not full facial expressions[]. The present study therefore adds to this knowledge with the more subtle facial micro-expression.
Micro Expression Emotions
There is also a lack of evidence of benefit to communication behaviour in this study. The ethos of breaking down communication into micro-skills is the basis for one of the most frequently used guides for clinical communication skills training in undergraduate medical education, the Calgary Cambridge Guides[27]. This project is an attempt to understand the cognitive basis for one of the micro-skills involved in communication, micro-expression perception, and the ability to improve that micro-skill through training.
Conclusion
This pilot study provides initial evidence that after training in the recognition of static facial micro-expressions medical students identified as poor communicators do not improve whilst those identified as good at communication do. This finding should be further explored to understand the basis of this difference and how best to target training for future medical undergraduates. Further, the impact of such training on clinical communication should be assessed.
Competing interests
The authors declare that they have no competing interests, including no connections with the Paul Ekman Group.
Authors' contributions
JE organized and ran the study and drafted an early version of this manuscript. AL made substantial contributions to the concept and design of the study and revised this manuscript. All authors read an approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors would like to thank Gerry Humphris for guidance during the study and on draft versions of this manuscript.
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