No open-access location is known for this record yet.
No open-access location is known for this record yet.
PURPOSE OF REVIEW: Social media has transformed how patients access and interpret gynecological health information, significantly influencing their expectations and medical decision-making. This comprehensive review examines how social media impacts patients' understanding of diagnoses, pursuit of treatment options, and interactions with healthcare providers. The increasing reliance on online content presents challenges, particularly when patients prioritize social media content over evidence-based recommendations. Given the rapid evolution of digital platforms, it is essential to understand the current trends and their impact on clinical practice. RECENT FINDINGS: Recent studies demonstrate that while social media offers unprecedented access to health information and community support, it simultaneously propagates misinformation that can adversely affect clinical encounters. Patients frequently turn to platforms such as TikTok, Instagram, X (formerly Twitter), and YouTube for gynecologic health information, though much of this content is anecdotal and lacks scientific validity. Research shows that while these platforms offer a wealth of information, the quality of this information is inconsistent, often leading to misconceptions about medical conditions and treatments. Healthcare providers face the dual challenge of addressing misconceptions while leveraging these platforms to enhance patient education and shared decision-making. SUMMARY: Understanding the influence of social media can help improve the accuracy of online health information and reduce stigma and social barriers surrounding gynecologic issues. Strengthening digital literacy and integrating reliable online resources into clinical practice can enhance patient education and promote informed decision-making in gynecology and gynecologic surgery.
Loading…
Stored only when both papers are in the corpus — 10 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.