ObjectiveThe priorities of people with mental health challenges should be reflected in the research conducted on their behalf. Quantifying alignment of priorities with the unmet needs of people with lived experience is challenging, and to our knowledge, such alignment has not been extensively studied in bipolar disorder (BD). Natural language processing approaches comparing common topics derived from public forums to those of biomedical research could help in identifying topics that are underaddressed.MethodsWe contrasted 5 years of lived experience questions posed during a Collaborative RESearch Team to study psychosocial issues in Bipolar Disorder (CREST.BD) "Ask Me Anything" (AMA) event hosted via Reddit (2019-2023) with topics labelled from abstracts extracted from PubMed with the search term BD during the same period. We applied topic modelling using BERTopic to identify dominant themes within each corpus and compared their semantic similarity using vector-based cosine similarity analyses.ResultsThe Reddit AMA data included 6159 comments, and the medical literature from this period included 9188 abstracts. Topic modelling and similarity analyses indicated that shared and frequent topics in both corpuses were sleep, BD medication safety in pregnancy, and lithium treatment. Topics with comparatively higher frequency in the Reddit forums than in medical research included BD misdiagnosis, marijuana and BD, and coping with daily challenges.DiscussionNotwithstanding limitations, comparing a corpus of lived experience questions with contemporaneous medical literature revealed areas of overlap, but some lived experience queries were not well covered in the biomedical literature. Natural language processing of public forums may facilitate identifying unmet priorities in BD.
Badal et al. (Fri,) studied this question.