METT(Micro-Expression) and SETT (Subtle-Expression) are a set of techniques collectively known as FACS, a tool used by professionals to recognize subconscious displays of emotion. Dr. Paul Ekman developed the system in 1978. The program garnered enough interest so that in 2009, Dr. Paul Ekman himself became the subject of a Fox television series entitled "Lie to Me". The character developed a fictitious FACS after its creator granted a patient a furlough only to have the patient commit suicide.
In reality, Dr. Ekman studied several populations, including mental health patients, spanning the globe in order to achieve a baseline of emotional expressions consistent across the species. Utilizing the data, he went on to establish his facial coding system, which is now used by professionals all over the world. Dr. Ekman's system has real world applications ranging from mental health to law enforcement - and yes - UX Research. Researchers trained in the techniques can better query their subjects when they observe deviations in reporting.
In activities such as card sorting, we can better judge whether the subject's responses are a result of biases such as groupthink, or other external influences. With skilled observation, FACS, SETT and METT could help us readily identify whether a respondent's choices are based on, or influenced by other respondent's in the room. We could read the respondent's face on a usability test, and note whether the respondent's answers align with their SE's and ME's. We could better determine if they are withholding relevant criticisms for any untold reasons, effectively allowing us to gain deeper insights by querying to uncover those criticisms. By prompting our audience we uncover what they're truly thinking and feeling during usability tests and other activities.
In short, utilizing tools such as SETT, METT, and FACS in conjunction with other existing research methodologies would potentially heighten the veracity of UX research findings. It could also potentially reduce biases that might unwittingly affect research outcomes. By employing FACS, researchers would now have a useful tool in their arsenal to help magnify emotional aspects of the process that were previously overlooked. Researchers would have the ability to query subjects on the spot upon observing emotional biases, without effecting the overall outcome of UX research studies. This would help ensure a higher quality outcome for all parties involved.
Post-test reports would represent more accurate data. The data would be more meaningful, if not critical, for the designer. That would translate into a better designed finished product. And for the user, that would translate into a better user experience. Some foreseeable limitations do exist, particularly where test sessions are performed remotely, rather than in-person. However, that could be easily overcome using existing devices such as webcams. The issue lies in existing remote usability testing platforms such as Usertesting.com, TryMyUI.com, Usertest.io, and others which currently do not facilitate querying testers in real-time.
Suggested Reading:
About Paul Ekman. Retrieved from https://www.paulekman.com/about/paul-ekman/
Wolf, K. (2015). Measuring facial expression of emotion. [online] PubMed Central (PMC). Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4734883/ [Accessed 11 Dec. 2018].
Ekman, P. (2015). Emotion in the human face (2nd ed.). Malor Books.
