Negative bias in facial emotion recognition is a well-established concept in mental disorders such as depression. However, existing face sets of emotion recognition tests may be of limited use in international research, which could benefit from more contemporary and diverse alternatives. Here, we developed and provide initial validation for the P1vital® Affective Faces set (PAFs) as a contemporary alternative to the widely-used Pictures of Facial Affect (PoFA).
The PAFs was constructed of 133 color photographs of facial expressions of ethnically-diverse trained actors and compared with the PoFA, comprised of 110 black and white photographs of facial expressions of generally Caucasian actors. Sixty-one recruits were asked to classify faces from both sets over six emotions (happy, sad, fear, anger, disgust, surprise) varying in intensity in 10% increments from 0 to 100%.
Participants were significantly more accurate in identifying correct emotions viewing faces from the PAFs. In both sets, participants identified happy faces more accurately than fearful faces, were least likely to misclassify facial expressions as happy and most likely to misclassify all emotions at low intensity as neutral. Accuracy in identifying facial expressions improved with increasing emotion intensity for both sets, reaching peaks at 60 and 80% intensity for the PAFs and PoFA, respectively. The study was limited by small sizes and age-range of participants and ethnic diversity of actors.
The PAFs successfully depicted a range of emotional expressions with improved performance over the PoFA and may be used as a contemporary set in facial expression recognition tests.