AI based sentiment analysis of online discussions related to cervical brachytherapy

Purpose/Objective(s)

Few studies have documented the experiences of patients receiving cervical brachytherapy. While evidence regarding quality of life issues in this population has emerged, traditional structured questionnaires often fail to capture the full range of patient perspectives. We hypothesized that analyzing unfiltered patient discussions from online forums would reveal unique insights into patient experiences, including previously unidentified emotional responses, concerns, and coping strategies. This study applied an artificial intelligence (AI) workflow to analyze cervical cancer and brachytherapy discussions from an online forum.

Materials/Methods

We extracted posts and comments from the subreddit r/cervicalcancer, focusing on discussions about brachytherapy between November 2020 and January 2024. We applied a processing pipeline to prepare the data for analysis. The content was analyzed using RoBERTa, a pre-trained deep learning model, to categorize sentiments as positive, negative, or neutral. We further evaluated posts using pre-defined keyword tagging to identify dominant topics within conversations based on recent literature.

Results

The analysis encompassed 898 unique posts and comments from an initial dataset of 1075 entries. Overall sentiments were categorized as 40.4% positive, 29.9% negative, and 29.7% neutral. Discussions related to “Bowel Domain” showed the highest proportion of negative sentiments (51.2%) among all topics. “Urinary Domain” (46.8%), “Pain” (43.4%), “Fatigue” (42.4%), and “Anesthesia” (41.4%) discussions also reflected predominantly negative sentiments. In contrast, “Recovery” and “Survivorship” discussions were predominantly positive. The sentiments on “Sex” and “Mental Health” related topics displayed a more balanced distribution between positive and negative perspectives.

Conclusion

Our study demonstrates the value of analyzing unstructured patient narratives from online forums related to cervical brachytherapy. We identified patterns of concerns that can inform clinical practice, particularly regarding patient education about bowel and urinary side effects. These findings can improve informed consent discussions and help clinicians better address patients’ significant concerns. Further work will focus on developing automated systems to bridge the gap between clinicians’ understanding and patients’ lived experiences.