Behind the Mask: Emotion Recognition in Healthcare Students

• Authors: Stephen Nowicki Jr., Emory University; Marco Bani, Università degli Studi di Milano-Bicocca; Selena Russo, Università degli Studi di Milano-Bicocca; Stefano Ardenghi, Università degli Studi di Milano-Bicocca; Giulia Rampoldi, Università degli Studi di Milano-Bicocca; Virginia Wickline, Georgia Southern University–Armstrong Campus; Stephen Nowicki, Emory University; Maria Grazia Strepparava, Università degli Studi di Milano-Bicocca
• Journal Title: Medical Science Educator
• Volume: Volume 31, Number 4
• Publisher: (publisher) | 2021-08-01, Pages 1273-1277
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1007/s40670-021-01317-8
• Subjects: Health Sciences, Medicine and Surgery; Psychology, General
• Keywords: Facemask; Emotion recognition; DANVA2; Medical education; Doctor patient communication

Abstract

Current widespread facemask usage profoundly impacts clinical practice and healthcare education where communicational dimensions are essential to the care and teaching processes. As part of a larger study, 208 medical and nursing students were randomly assigned to a masked vs unmasked version of the standardized facial emotion recognition task DANVA2. A significantly higher number of errors existed in the masked vs unmasked condition. Differences for happy, sad, and angry faces, but not for fearful faces, existed between conditions. Misinterpretation of facial emotions can severely affect doctor-patient and inter-professional communication in healthcare. Teaching communication in medical education must adapt to the current universal use of facemasks in professional settings.