Monday, November 2, 2020

Faces of clinical pain: inter‐individual facial activity patterns in shoulder pain patients

Abstract

Background

Facial activity during pain is composed of varying combinations of a few elementary facial responses (so called Action Units). A previous study of experimental pain showed that these varying combinations can be clustered into distinct facial activity patterns of pain. In the present study, we examined whether comparable facial activity patterns can also be identified among people suffering from clinical pain; namely shoulder pain.

Methods

Facial expressions of patients suffering from shoulder pain (N=126) were recorded while twice undergoing a battery of passive range‐of‐motion‐tests to their affected limbs (UNBC‐McMaster Shoulder Pain Expression Archive Database), which elicited peaks of acute pain. Facial expressions were analysed using the Facial Action Coding System to extract facial Action Units (AUs). Hierarchical cluster analyses were used to look for characteristic combinations of these AUs.

Results

Cluster analyses revealed four distinct activity patterns during painful movements. Each cluster was composed of different combinations of pain‐indicative AUs, with one AU common to all clusters, namely “narrowed eyes”. Besides these four clusters, there was a “stoic” pattern, characterized by no discernible facial action. The identified clusters were relatively stable across time and comparable to the facial activity patterns found previously for experimental heat pain.

Conclusions

These findings corroborate the hypothesis that facial expressions of acute pain are not uniform. Instead, they are composed of different combinations of pain‐indicative facial responses, with one omnipresent response, namely “narrowed eyes”. Raising awareness about these inter‐individually different “faces of pain” could improve the recognition and, thereby, its diagnostic training for professionals, like nurses and physicians.



from Wiley: European Journal of Pain: Table of Contents https://ift.tt/35Ufaip
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