Chronic Pain and Language: A Topic Modelling Approach to Personal Pain Descriptions

TL;DR

This paper introduces a topic modeling approach to analyze verbal descriptions of chronic pain, aiming to uncover patterns that can improve understanding and management of this subjective health issue.

Contribution

It presents a novel application of topic modeling to chronic pain descriptions, providing new insights into pain experiences for clinical assessment.

Findings

Identified distinct patterns in pain descriptions

Quantified pain experiences using latent space analysis

Provided clinically relevant insights for pain management

Abstract

Chronic pain is recognized as a major health problem, with impacts not only at the economic, but also at the social, and individual levels. Being a private and subjective experience, it is impossible to externally and impartially experience, describe, and interpret chronic pain as a purely noxious stimulus that would directly point to a causal agent and facilitate its mitigation, contrary to acute pain, the assessment of which is usually straightforward. Verbal communication is, thus, key to convey relevant information to health professionals that would otherwise not be accessible to external entities, namely, intrinsic qualities about the painful experience and the patient. We propose and discuss a topic modelling approach to recognize patterns in verbal descriptions of chronic pain, and use these patterns to quantify and qualify experiences of pain. Our approaches allow for the extraction of novel insights on chronic pain experiences from the obtained topic models and latent spaces. We argue that our results are clinically relevant for the assessment and management of chronic pain.