Evaluating perception of pain-related social stimuli

National Center For Complementary & Integrative Health

Investigators

Abstract

The treatment and assessment of pain is subject to health disparities. To date, our ability to study the social processes that give rise to these disparities in laboratory settings has been limited due to a lack of diverse datasets of facial expressions of pain. These conclusions about how individuals respond to others in pain have been limited to stimuli that involve actors or computer-generated stimuli. We and others recognized this gap in the literature and have recently collected video data from real participants undergoing painful and nonpainful stimulation (protocol 17-AT-0155, “Sociocultural & Biobehavioral Influences on Pain Expression and Assessment”). Our participants were able to opt in or out of having their data included in a database of facial pain expressions. In this IRB-exempt project, we now seek to understand how these stimuli are perceived and evaluated, and how they compare to other published datasets of pain and or other emotional expressions. We will use programs such as Amazon's Mechanical Turk to evaluate how these images are perceived, to test whether different psychological and sociodemographic factors affect pain assessment, and to collect normed ratings of social stimuli for use in stimulus selection in subsequent individual studies. During the past year, we began data collection on this IRB-exempt protocol. We conducted a of series online studies in which participants viewed videos of other individuals, and rated whether the subject was in pain or not, the intensity of the pain, and their confidence in that rating. They also rated perceived similarity and completed personality questionnaires. Upon completion of data collection, we will use these results to determine whether social factors affect pain assessment, to select normed stimuli for future studies, and to provide normed ratings for inclusion in a publicly available dataset which we hope to release in the FY26. We have also used this protocol to ensure our findings from Sub-study 2 replicate in a new participant pool. We again found similar pain assessment biases. We are now planning a third online study that tests the same effects but uses different example trials to ensure the stability and robustness of our findings of biases in pain assessment.