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Camille Saumure, Marie-Pier Plouffe-Demers, Daniel Fiset, Stéphanie Cormier, Miriam Kunz, Caroline Blais; The impact of gender on visual strategies underlying the discrimination of facial expressions of pain.. Journal of Vision 2019;19(10):154c. doi: https://doi.org/10.1167/19.10.154c.
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© ARVO (1962-2015); The Authors (2016-present)
Previous studies have found a female advantage in the recognition/detection (Hill and Craig, 2004; Prkachin et al., 2004) of pain expressions, although this effect is not systematic (Simon et al., 2008; Riva et al., 2011). However, the impact of gender on pain expression recognition visual strategies remains unexplored. In this experiment, 30 participants (15 males) were tested using the Bubbles method (Gosselin & Schyns, 2001), which randomly sampled facial features across five spatial frequency (SF) bands to infer what visual information was successfully used. On each of the 1,512 trial, two bubblized faces, sampled from 8 avatars (2 genders; 4 levels of pain intensity), were presented to participants who identified the one expressing the highest pain level. Three difficulty levels, determined by the percentage of pain difference between the two stimuli (i.e 100%, 66% or 33%) were included. Number of bubbles needed to maintain an average accuracy of 75% was used as a performance measure (Royer et al., 2015). Results indicated a trend towards a higher number of bubbles needed by male (M=57.7, SD=30.4) in comparison to female (M=40.2, SD=23.2), [t(28)=2.02,p=0.05]. Moreover, this difference was significant with the highest level of difficulty [t(28)=2.22, p=0.04], suggesting that pain discrimination was more difficult for male (M=77.6, SD=36.8) than female (M=52.3, SD=24.5). Classification images, generated by calculating a weighted sum of the bubbles position (where accuracies transformed in z-scores were used as weights), revealed that female made a significantly higher use of the lowest band of SF (Zcrit = 2.7, p< 0.05; 5.4–2.7 cycles per face). These results suggest that gender impacts the performance and the visual strategies underlying pain expression recognition.
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