Sociocultural & biobehavioral influences on pain expression and assessment

National Center For Complementary & Integrative Health

Investigators

Linked publications, trials & patents

Abstract

This protocol measures pain-related facial responses in a diverse population to measure whether nonverbal responses to pain vary as a function of biological and sociocultural factors. We will then measure whether individuals pay attention to different features of pain or assess pain differently in in-group relative to out-group individuals, and whether we can develop interventions to reduce any biases in pain assessment accuracy. During FY25, we completed data analysis from the protocol’s first third sub-study and prepared a manuscript for publication. We also began piloting and data-collection for the protocol’s fourth sub-study, which measures brain mechanisms of social learning and feedback-based improvements in pain assessment accuracy. We continued analyses of facial movement and physiological responses from the first-substudy, and conducted an online study to test whether findings from our second sub-study replicate in a new sample. Sub-study 1 measures the association between noxious stimuli, pain, and facial responses. The PhD student who led the study graduated and started a postdoctoral fellowship during FY23, but has remained a collaborator as new fellows in the lab analyze remaining data. During FY25, we compared different software algorithms to assess facial movements, and will complete initial analyses by the end of FY25. A postdoc who will be starting in FY25 will use machine learning to determine which facial movement features best predict subjective pain, and the extent to which these expressions are common across social groups. Following completion, sub-study 1 participants were asked whether they want their images to be included in a database that will be shown to other participants. We are currently using these images in an online study to gather normed ratings and will be producing a publicly available database within the next year. Images of a subset of sub-study 1 participants who opted into the database were used as stimuli for a subsequent sub-study 2, which measured how individuals view and judge pain in others that they perceive to be similar or different from them, and sub-study 3, which evaluated whether feedback improves pain assessment accuracy. Sub-study 2 results were submitted in FY23 (Dildine et al., PsyArXiv) and we have replicated these findings in an online follow up study. We plan to test for replication with a different subset of stimuli, and then will prepare a comprehensive manuscript for submission. During FY25, we focused on data analysis for sub-study 3, and will submit a manuscript before the end of FY25. Healthy volunteers (perceivers) viewed videos of sub-study 1 participants (targets) experiencing pain and evaluate pain using the same scales as the targets. Half the participants received feedback about the targets actual pain on every trial, whereas half the participants received no feedback. Feedback improved pain assessment accuracy, whether we examined binary choices (pain/no pain) or accuracy of pain intensity assessments. We are preparing a manuscript on these results and the impact of perceived similarity (Zhao et al., In prep). We also find that pupil dilation differs as a function of whether an individual perceives pain or not, and are currently analyzing eye tracking data to determine the relationship between gaze position, facial expression, and pain assessment accuracy. Finally, we have collaborated with Dr. Angela Langdon (NIMH) to develop a computational model of the relationship between facial movement and pain assessment, and are currently preparing this manuscript for preparation (Dadbhawala et al., In prep). We have developed a within-subjects version of this task that elicits similar differences between feedback-driven and uninstructed social learning which is adapted for the fMRI environment. We have completed two pilot studies to optimize the task and fMRI data collection will be underway before the end of FY25, with the goal of completing data collection and analyses during FY26.