Functional Register in Reddit-Based Medical Consultations: A Systemic Functional Linguistics Perspective - Rohmah, Maulidatur; Sugiharti, Dona Rahayu (Proceeding of Undergraduate Conference on Literature, Linguistic, and Cultural Studies, 2025)
This research aims to analyze the use of registers in online medical consultations on Reddit’s r/AskDocs, focusing on identifying the types of registers used by medical professionals and patients, as well as examining their contextual meanings. The urgency of this study stems from the increasing reliance on digital health platforms, which necessitates a deeper understanding of how language functions in virtual healthcare interactions. In online spaces, where communication occurs asynchronously and without face-to-face cues, the choice of language plays a crucial role in delivering clear and empathetic health information. This study is grounded in Halliday’s theory of register, which breaks down language variation into three components: field (the subject matter of discourse), tenor (the relationships between participants), and mode (the channel of communication). Using a qualitative descriptive approach, this research collected 100 posts from r/AskDocs throughout 2024, selected based on the relevance and presence of medical vocabulary. The analysis found 22 frequently occurring register-related keywords, including discharge (9 times), negative (13 times), positive (15 times), and test (18 times), which are arranged alphabetically to aid clarity. These terms demonstrate semantic shifts when placed in medical contexts—for example, “negative” no longer conveys a generally undesirable condition, but rather signifies the absence of disease. Such shifts indicate a specialized use of language that differs from everyday meanings. Ultimately, the findings show that language in online medical consultations is purposefully crafted to maintain professionalism, clarity, and empathy. This research contributes to sociolinguistic scholarship by offering insights into how linguistic strategies function in digital medical discourse, and how register theory can be effectively applied to analyze online healthcare interactions.