Characterizing Patient Questions Before and After Rhinoplasty on Social Media: A Big Data Approach.

Abstract

As an aesthetic surgery, a successful rhinoplasty is often assessed by patient satisfaction, subject to a diverse array of qualitative factors including patient expectations and happiness with care provided. While substantial effort has been dedicated to understanding patients' post-operative concerns, addressing patients' pre-operative questions has been comparatively less studied. This study analysed pre- and post-operative questions about rhinoplasty on social media to gain insights into patients' concerns and develop targeted educational material. The most viewed rhinoplasty questions on Realself.com, a social media platform for discussions about cosmetic surgeries, were collected and analysed. Questions were then stratified into pre- and post-operative and further assigned categories based on common topics found in the data. Using a machine learning approach, the most common pre- and post-operative questions were determined. 2014 rhinoplasty questions were collected in total, with 957 pre-operative and 1057 post-operative. The most commonly asked pre-operative questions were about appearance (n = 441, 46.1%), function (n = 102, 10.7%), and cost (n = 94, 9.8%). The most commonly asked post-operative questions were about appearance (n = 502, 47.5%), behaviour allowed/disallowed (n = 283, 26.8%), and symptoms after surgery (n = 235, 22.2%). An educational handout with the 10 most common pre- and post-operative questions was developed using machine learning analysis, with the majority of questions about appearance. Patients primarily expressed concern about appearance when asking questions about rhinoplasty on social media, along with other aspects of their pre- and post-operative course. The educational handout developed by this study can be applied to address commonly asked patient questions during pre-operative education. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .