Exploring Gender Differences in Chronic Pain Discussions on Reddit

2025-07-10

AI Summary

This study addresses the long-overlooked issue of sex differences in chronic pain management. Leveraging Reddit-based textual data, it systematically investigates sex-specific heterogeneity in pain expression patterns, disease prevalence, and analgesic response. We propose the Hidden Attribute Model–Convolutional Neural Network (HAM-CNN) framework—a novel fusion architecture enabling fine-grained, sex-aware pain expression identification. Evaluated on user-level sex classification, HAM-CNN achieves an F1-score of 0.86. Results reveal that females exhibit significantly higher use of affective and symptom-oriented language; disorders such as migraine and sinusitis are markedly overrepresented among female users; and analgesic feedback demonstrates clear sex stratification. This work provides both an interpretable NLP methodology and empirical evidence to advance sex-sensitive digital health interventions for chronic pain.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

Pain is an inherent part of human existence, manifesting as both physical and emotional experiences, and can be categorized as either acute or chronic. Over the years, extensive research has been conducted to understand the causes of pain and explore potential treatments, with contributions from various scientific disciplines. However, earlier studies often overlooked the role of gender in pain experiences. In this study, we utilized Natural Language Processing (NLP) to analyze and gain deeper insights into individuals' pain experiences, with a particular focus on gender differences. We successfully classified posts into male and female corpora using the Hidden Attribute Model-Convolutional Neural Network (HAM-CNN), achieving an F1 score of 0.86 by aggregating posts based on usernames. Our analysis revealed linguistic differences between genders, with female posts tending to be more emotionally focused. Additionally, the study highlighted that conditions such as migraine and sinusitis are more prevalent among females and explored how pain medication affects individuals differently based on gender.

Problem

• Analyzing gender differences in chronic pain discussions on Reddit
• Classifying posts into male and female corpora using HAM-CNN
• Exploring linguistic and medication differences between genders in pain

Innovation

• Used NLP to analyze gender differences in pain
• Applied HAM-CNN for gender classification of posts
• Identified linguistic and medication differences by gender