Behind the mask: Emotion recognition in healthcare students

Background: The current widespread and compelled usage of facemasks may have a deep impact in healthcare and educational contexts where relational and communicational dimensions are essential to the process of care and teaching. Nevertheless, little is known about the effect of facemask wearing on emotion recognition. In a cross-sectional study, we assessed the impact of facemasks on emotion recognition in healthcare students of a North Italian University. Methods: As part of an in-progress study, out of the 1572 medical and nursing students invited to take part in the study, 208 completed the study survey. Participants were randomly assigned to a masked vs unmasked version of the widely used and standardized emotion recognition task (DANVA2) that presents 24 faces expressing four emotions (happiness, fear, anger, sadness) with high and low intensity. Findings: A statistically significant higher number of errors in the masked (9.6 ±2.21) vs unmasked condition (4.96 ±2.78) (t(206) = -13.25, p ≤ .001) was found. A significant difference for happy (t(206) = -13.2, p ≤ .001), sad (t(206) = -4.54, p ≤ .001) and angry (t(206) = -12.05, p ≤ .001) faces but not for fearful (t(206) = -1.5, p = .134 ns) faces was found between conditions. When gender type of course (medical vs nursing) and year of course were examined, no difference has been found. Discussion: Teaching communication in the healthcare context must be adapted to the new situation that requires the universal use of facemask. The higher risk of misinterpretation of facial emotion can cause severe problems in terms of doctor-patient communication and intra/interprofessional communication. Healthcare teachers and students should be trained to express and recognize emotions in masked conditions.