SEX AND RACE DIFFERENCES IN RATING OTHERS' PAIN, PAIN-RELATED NEGATIVE MOOD, PAIN COPING, AND RECOMMENDING MEDICAL HELP.

This study examined the influence of Virtual Humans' (VH) sex and race on participants' ratings of pain intensity, pain unpleasantness, pain-related negative mood, pain coping, and recommendations for medical help. Seventy-five undergraduates viewed a series of VHs and provided computerized visual analog scale (VAS) ratings for the five domains listed above. Mixed model ANOVA analyses showed that participants of both sexes and races viewed female VHs as experiencing greater pain intensity, greater pain unpleasantness, a greater number of pain-related negative moods, poorer coping skills, and a greater need to seek medical help for their pain. Participants of both races rated Caucasian VHs as experiencing more negative moods and poorer coping skills do deal with their pain. The novel computerized VH technology used herein allowed for the standardization of pain expression across sexes and races of VH stimuli, thus allowing us to remove the influence of biases when creating the study stimuli. This is a notable advantage over other research methodologies in this line of inquiry. Several future research and education applications of this VH technology are discussed.