The ability to recognise emotions of others is important but can get lost in translation, so a new study develops a face-based test not affected by linguistic differences.
The ability to recognise emotions expressed by others is vital for job performance and career success, but can be contaminated by linguistic differences in an era where people increasingly work in a language other than their mother tongue. Like many other things, emotions can be ‘lost in translation’ between languages.
A new study co-authored by Dr Jochen Menges of Cambridge Judge Business School addresses this issue by developing and validating a face-based, non-linguistic test of what is known in psychology as ERA-O – the emotional recognition ability of emotions expressed by other people.
The new Face-based Emotion Matching Test (FEMT) is detailed in a study published in the European Journal of Psychological Assessment.
“This newly validated tool will allow testing of people’s ability to read emotions regardless of linguistic differences, and that is really important in a time when empathic leadership is ever more needed in the modern workplace of different nationalities and now increased remote working,” says Dr Jochen Menges, University Lecturer in Organisational Behaviour at Cambridge Judge Business School and Chair of Human Resource Management and Leadership at the Department of Business Administration of the University of Zurich.
“While algorithms may allow automation of many routine tasks, many jobs will still demand emotional intelligence and social perception – and this new test measures that based on facial expression rather than language in a way that will be useful for many organisations.”
The new test was developed by asking 654 working adult participants to match adult faces that display 32 pairs of facial emotion expressions – 16 pairs featuring the same emotions and 16 pairs featuring different emotions – including pairs of negative emotions which have a higher rate of misclassification such as contempt vs disgust, disgust vs anger, surprise vs fear, sadness vs. fear, and contempt vs anger.
Rather than being asked (as in traditional tests) to linguistically label the expressed emotion, the new test instead asks participants to assess whether for each pair the two images featured the same, somewhat different, or different emotions.
The study then validated the new test in relation to emotional intelligence and the ‘Big Five’ personality traits commonly used by psychologists (extraversion, agreeableness, openness, conscientiousness, and neuroticism). This validation entailed assessing the overlap with existing measures of emotion recognition ability, as well as the distinctness of the new measure.
The researchers found that scores on the new tests relate to coworker assessments of the participants on social astuteness (sample query: “this person is particularly good at sensing the motivations and hidden agendas of others”) and adaptive performance in the workplace (“this person successfully handles emergencies, interruptions, and losses at work”).
“The FEMT can assist in the process of hiring potentially successful personnel,” the study concludes. “Organisations might apply the FEMT when hiring employees for roles where emotion recognition ability may enhance performance, such as jobs that demand complex social perception in enterprising and social work environments. Supplemented by other sources of information, such as cognitive intelligence tests and interviews, the FEMT can make the recruitment and selection process more efficient.”
The study – entitled “It works without words: a nonlinguistic ability test of perceiving emotions with job-related consequences” – is co-authored by Profesor Gerhard Blickle, Dr Iris Kranefeld and Bastian P. Kückelhaus of the University of Bonn; Andreas Wihler of the University of Exeter; and Dr Jochen Menges of Cambridge Judge Business School and the University of Zurich.