Abstract
Pain assessment and treatment is challenging and can be influenced by patient demographic characteristics. However, these influences have received little empirical attention, particularly in a healthcare student population. This online study investigated the effects of patients' sex, race, age, and pain expression on healthcare students' assessment of pain and pain-related sequelae using virtual human (VH) technology. A LENS model design captured decision-making policies at the nomothetic and idiographic level.
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