Patient experiences in the cochlear implant Reddit community: Comparing human and large language model categorization
American Journal of Audiology, 2026
In this analysis of 996 posts from r/Cochlearimplants, five major themes emerged: community engagement and support (N = 944, 94.8%), medical/surgical journey (N = 463, 46.5%), device/technical issues (N = 343, 34.4%), daily life/adjustments (N = 236, 23.7%), and media/outreach (7.2%, N = 72). OpenAI o3 and Gemini 2.5 Pro showed the highest agreement with human coders (κ = 0.35 and 0.34, respectively) compared to Claude Sonnet 4 (κ = 0.25). Compared to a median of 8.75 hours per human annotator (>50hrs total), each large language model (LLM) completed the annotation in under 20 minutes. These findings highlight both the richness of online CI discourse and the growing potential of LLMs to support large-scale qualitative analysis with verification via human oversight to guide patient-centered clinical support, education, and medical device improvements.
Recommended citation: Habib DRS, Depala K, Lin J, Le S, McFall N, Dewan SS, Huang J, Habib MWS, Bishay AE, Siebor K, Demiroz GB, Chowdhury NI, Moberly AC. Patient experiences in the cochlear implant Reddit community: Comparing human and large language model categorization. Am J Audiol. 2026. doi:10.1044/2025_AJA-25-00216