LLMs Pick Up Cues of Potential Comorbid ADHD in People Reporting Anxiety when Keywords Are Not Enough
Track: Non-traditional track
Keywords: adhd, anxiety, reddit
Abstract: We present a novel task that can elucidate the connection between anxiety and ADHD; use Transformers to make progress
toward solving a task that is not solvable by keyword-based classifiers; and discuss a method for visualization of our classifier
illuminating the connection between anxiety and ADHD presentations.
Up to approximately 50\% of adults with ADHD may also have an anxiety disorder and approximately 30\% of adults with anxiety may also have ADHD. Patients presenting with anxiety may be
treated for anxiety without ADHD ever being considered, possibly affecting treatment. We show how data that bears on ADHD that is comorbid with anxiety can be obtained from social media data, and show that Transformers can be used to detect a proxy for possible comorbid ADHD in people with anxiety symptoms.
We collected data from anxiety and ADHD online forums (subreddits). We identified posters who first started posting in the
Anxiety subreddit and later started posting in the ADHD subreddit as well. We use this subset of the posters as a proxy for
people who presented with anxiety symptoms and then became aware that they might have ADHD.
We fine-tune a Transformer architecture-based classifier to classify people who started posting in the Anxiety subreddit and then
started posting in the ADHD subreddit vs. people who posted in the Anxiety subreddit without later posting in the ADHD
subreddit.
We show that a Transformer architecture is capable of achieving reasonable results (76\% correct for RoBERTa vs.
under 60\% correct for the best keyword-based model, both with 50\% base rate).
Disclosure: this paper was accepted at CLPsych @ EACL with the title ``Detecting a Proxy for Potential Comorbid ADHD in People Reporting Anxiety Symptoms from Social Media Data"
Presentation And Attendance Policy: I have read and agree with the symposium's policy on behalf of myself and my co-authors.
Ethics Board Approval: No, our research does not involve datasets that need IRB approval or its equivalent.
Data And Code Availability: Yes, we will make data and code available upon acceptance.
Primary Area: General machine learning for healthcare (i.e. none of the above)
Student First Author: No, the primary author of the manuscript is NOT a student.
Submission Number: 47
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