Probing Public Perceptions of Antidepressants on Social Media: Mixed Methods Study

Area of Science:

• Psychiatry and Mental Health
• Computational Social Science
• Patient-Reported Outcomes

Background:

• Antidepressants are vital for major depressive disorder (MDD) management.
• Patient nonadherence is a significant challenge, often stemming from side effect concerns, dependency fears, and efficacy doubts.
• Patient-centered care, prioritizing individual needs, is essential for improving treatment adherence and satisfaction.

Purpose of the Study:

• To deeply explore patient experiences with antidepressants.
• To provide actionable insights for healthcare providers, families, and communities to create personalized treatment strategies.
• To enhance patient satisfaction and adherence through integrated patient-centered care.

Main Methods:

• Analysis of patient discussions from AskaPatient and Reddit using natural language processing (NLP) and large language models (LLMs).
• Application of sentiment analysis, emotion detection, personality profiling, and topic modeling.
• Examination of demographic variations in patient experiences with antidepressants.

Main Results:

• A majority of discussions (59.3%) showed neutral sentiment, with significant negative sentiment (38.4%).
• Fear (44.66%) and sadness (34.49%) were the predominant emotions detected.
• The leading topic was "Mental Health and Relationships" (11.69%), with nonadherence discussions dominated by fear and sadness.

Conclusions:

• Psychological insights into public perceptions of antidepressants are crucial.
• Findings support the development of tailored, patient-centered treatment approaches.
• Enhanced empathy and effectiveness in care can be achieved by aligning treatments with individual patient needs.