Characterizing Patient Questions Before and After Rhinoplasty on Social Media: A Big Data Approach.
Abstract
[BACKGROUND] 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.
[METHODS] 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.
[RESULTS] 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.
[CONCLUSIONS] 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.
[LEVEL OF EVIDENCE V] 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 .
[METHODS] 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.
[RESULTS] 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.
[CONCLUSIONS] 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.
[LEVEL OF EVIDENCE V] 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 .
추출된 의학 개체 (NER)
| 유형 | 영어 표현 | 한국어 / 풀이 | UMLS CUI | 출처 | 등장 |
|---|---|---|---|---|---|
| 시술 | rhinoplasty
|
코성형술 | dict | 6 | |
| 약물 | Media
|
C0009458
Communications Media
|
scispacy | 1 | |
| 약물 | [BACKGROUND]
|
scispacy | 1 | ||
| 약물 | [RESULTS] 2014 rhinoplasty
|
scispacy | 1 | ||
| 약물 | [CONCLUSIONS] Patients
|
scispacy | 1 | ||
| 기타 | Patient
|
scispacy | 1 | ||
| 기타 | patients
|
scispacy | 1 |
MeSH Terms
Big Data; Humans; Patient Satisfaction; Rhinoplasty; Social Media; Surgery, Plastic; Treatment Outcome
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