Abstract
Non-steroidal anti-inflammatory drugs (NSAIDs) are used to manage pain and inflammation in pets, particularly for chronic conditions like osteoarthritis (OA) and acute post-surgical pain. Despite their efficacy, concerns regarding adverse effects, affordability and long-term safety drive pet owners to discuss their experiences online. This study employed social media listening (SML) to analyse online discussions about NSAIDs, leveraging large language models (LLMs) to classify posts and identify themes. In total, 15,921 posts were collected from X, Reddit, Facebook, blogs, forums, reviews and Threads. After pre-processing and zero-shot relevancy filtering, 9,434 posts were analysed using non-negative matrix factorisation (NMF) and LLM-driven thematic extraction. Key findings reveal pet owners frequently compare NSAID efficacy and safety, with carprofen, meloxicam and grapiprant discussed most. Gastrointestinal and renal issues emerged as concerning side effects, leading to increased interest in multimodal pain management, including cannabidiol (CBD), gabapentin, hydrotherapy and acupuncture. The high cost of NSAIDs drives demand for generic alternatives. This study underscores the value of SML and AI-driven data analysis in understanding real-world pet owner experiences. These insights can inform veterinary professionals and pharmaceutical companies, guiding strategies to improve pet owner education and medication accessibility, more effectively supporting owners’ concerns and advancing veterinary pain management approaches.