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

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.

Analysis of Chronic Pain Experiences Based on Online Reports: the RRCP Dataset

Chronic pain is recognized as a major health problem, with impacts at the economic, social, and individual levels. Being a private and subjective experience, dependent on a complex cognitive process involving the subject's past experiences, sociocultural embeddedness, as well as emotional and psychological loads, 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. Verbal communication is, thus, key to convey relevant information to health professionals that would otherwise not be accessible to external entities. Specifically, what a patient suffering of chronic pain describes from the experience and how this information is disclosed reveals intrinsic qualities about the patient and the experience of pain itself. We present the Reddit Reports of Chronic Pain (RRCP) dataset, which comprises social media textual descriptions and discussion of various forms of chronic pain experiences, as reported from the perspective of different base pathologies. For each pathology, we identify the main concerns emergent of its consequent experience of chronic pain, as represented by the subset of documents explicitly related to it. This is obtained via document clustering in the latent space. By means of cosine similarity, we determine which concerns of different pathologies are core to all experiences of pain, and which are exclusive to certain forms. Finally, we argue that our unsupervised semantic analysis of descriptions of chronic pain echoes clinical research on how different pathologies manifest in terms of the chronic pain experience.