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Currently accepted at: Journal of Participatory Medicine

Date Submitted: Oct 13, 2025
Open Peer Review Period: Oct 28, 2025 - Dec 23, 2025
Date Accepted: Feb 25, 2026
(closed for review but you can still tweet)

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/85812

The final accepted version (not copyedited yet) is in this tab.

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Exploring Peer Support and Side Effect Experiences in Antidepressant Discussions on Reddit: A Pilot Epistemic Network Analysis

  • Ejura Yetunde Salihu; 
  • Apoorva Reddy

ABSTRACT

Antidepressant use and withdrawal are often accompanied by side effects such as dizziness, weight gain, and sexual dysfunction. Antidepressants and associated side effects are stigmatized topics. Social media platforms like Reddit are considered "safe spaces" by users because they can freely share their experiences and receive support. This study analyzes discussions from the subreddit, r/depression, to examine how users talk about antidepressant side effects, withdrawal symptoms, and related experiences of depression. We scraped ten high-engagement threads from the subreddit r/depression using the Python wrapper for the Reddit API and conducted a two-step analysis. First, a pilot test was performed using Sertraline/Zoloft threads, followed by analysis of all antidepressant threads. A subset of data was hand-coded to create and validate regular expressions, which were then used to automatically code the remaining dataset. The resulting coded data were analyzed using Epistemic Network Analysis (ENA) and complemented with qualitative analysis, elements of semantic networks, and hypergraphs. We found that posts are more likely to discuss emotional flattening, sleep, and memory or brain issues. Additionally, references to dizziness tended to occur with discussions of withdrawal and offers of empathy, while reports of dream-related side effects and requests for personal experiences co-occurred frequently. With the additions of elements of semantic networks and hypergraphs, we deduced that offers of empathy occurred when users said they experienced dizziness caused by withdrawal, while mentions of brain zaps from withdrawals received teaching support. Study findings highlight how individuals experiencing antidepressant side effects and withdrawal symptoms use online forums like Reddit to seek validation, share coping strategies, and provide emotional support to others. The nuanced discussions observed, particularly around empathy, symptom management, and shared learning, underscore the role of peer-to-peer networks in normalizing stigmatized experiences and mitigating isolation associated with antidepressant use. Clinicians and digital health practitioners can leverage these insights to better understand patient language, emotional framing, and informational needs outside clinical settings.


 Citation

Please cite as:

Salihu EY, Reddy A

Exploring Peer Support and Side Effect Experiences in Antidepressant Discussions on Reddit: A Pilot Epistemic Network Analysis

JMIR Preprints. 13/10/2025:85812

DOI: 10.2196/preprints.85812

URL: https://preprints.jmir.org/preprint/85812

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