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

Trends and Preferences of Rhinoplasty Among Chinese Patients: A Social Media Analysis

BACKGROUND

This study investigated the trends, motivations and preferences of rhinoplasty in China.

METHODS

Data on rhinoplasty were collected from Xiaohongshu and analyzed for trends. Text analysis and word frequency statistics were performed on the notes and comments using Python modules.

RESULTS

We obtained 1065 notes with 102,153 comments, 239,383 collections and 640,579 likes. The number of rhinoplasty-related publications increased annually, correlating with per capita disposable income of households (DI) growth (r2 = 0.609, P = 0.041 < 0.05). In the Southern provinces, there was a notably higher volume of publications compared to the Northern provinces (P = 0.001). Furthermore, a significant correlation was observed between publication data, population size, and the DI (r2 = 0.786, P < 0.001). The nasal tip (3197) and nasion (1409) were the most mentioned nasal subunits. "Good-looking" (9672) and "natural" (2811) were the most used words to describe the nose shape. The "doctor" (4377), the "hospital" (2182) and "hyaluronic acid" (2106) were the most mentioned rhinoplasty procedure related vocabulary.

CONCLUSIONS

Discussions about rhinoplasty in China are increasing, and more people express their desire for rhinoplasty on social networks, related to China's DI growth. The Southern provinces show a higher inclination toward these discussions, a trend that correlates with our findings of a positive association between NOPs and both DI and population size. Netizens pay more attention to the shape of nasal tip and nasion, and prefer the good-looking and natural appearance. Most people consider autologous cartilage or hyaluronic acid injection for rhinoplasty. Doctors are the primary consideration for patients.

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 .

Machine learning analysis of online patient questions regarding breast reconstruction

BACKGROUND

Social media has become a dominant educational resource for breast reconstruction patients. Rather than passively consuming information, patients interact directly with other users and healthcare professionals. While online information for breast reconstruction has been analyzed previously, a robust analysis of patient questions on online forums has not been conducted. In this study, the authors used a machine learning approach to analyze and categorize online patient questions regarding breast reconstruction.

METHODS

Realself.com was accessed and questions pertaining to breast reconstruction were extracted. Data collected included the date of question, poster's location, question header, question text, and available tags. Questions were analyzed and categorized by two independent reviewers.

RESULTS

522 preoperative questions were analyzed. Geographic analysis is displayed in Figure 1. Questions were often asked in the pre-mastectomy period (38.3%); however, patients with tissue expanders currently in place made up 28.5%. Questions were often related to reconstructive methods (23.2%), implant selection (19.5%), and tissue expander concerns (16.7%). Questions asked in the post-lumpectomy period were significantly more likely to be related to insurance/cost and reconstructive candidacy (p < 0.01). The "Top 6″ patient questions were determined by machine learning analysis, and the most common of which was "Can I get good results going direct to implant after mastectomy?"

CONCLUSIONS

Analysis of online questions provides valuable insights and may help inform our educational approach toward our breast reconstruction patients. Our findings suggest that questions are common throughout the reconstructive process and do not end after the initial consultation. Patients most often want more information on the reconstructive options, implant selection, and the tissue expansion process.

Social Media Utilization in Otolaryngology: A Scoping Review

OBJECTIVE

Social media (SM) is an increasingly popular medium for the medical community to engage with patients, trainees, and colleagues. This review aimed to identify reported uses of SM in otolaryngology-head and neck surgery (OHNS), assess the quality of evidence supporting these uses, and identify gaps in the literature. With the relative lack of regulatory guidelines for the development of SM content, we hypothesized that the quality of content available on SM would be highly variable.

DATA SOURCES AND METHODS

A scoping review was performed of English-language peer-reviewed studies published to date discussing SM use in any form within OHNS. Three reviewers independently screened all abstracts. Two reviewers independently extracted data of interest from the full text of articles identified from the preliminary abstract screen.

RESULTS

171 studies were included, with 94 (54.9%) studies published between 2020 and 2022. 104 (60.8%) studies were conducted in the US. 135 (78.9%) used cross-sectional or survey-based methodology; only 7 (4.1%) were controlled studies. SM was most commonly employed for professional networking (n = 37 [21%]), and within subspecialties of otology (n = 38 [22%]) and rhinology/allergy (n = 25 [15%]). Facebook was most frequently used for study recruitment (n = 23 [13.5%]), YouTube for patient education (n = 15 [14.6%]), and Twitter for professional networking (n = 16 [9.4%]).

CONCLUSION

SM use within OHNS is increasing rapidly, with applications including patient education, professional networking, and study recruitment. Despite myriad articles, there remains a paucity of well-controlled studies. As SM becomes integrated into healthcare, particularly for applications directly impacting patient care, higher levels of evidence are needed to understand its true impact. Laryngoscope, 133:2447-2456, 2023.

Applications of Machine Learning in Facial Cosmetic Surgeries: A Scoping Review

OBJECTIVE

To review the application of machine learning (ML) in the facial cosmetic surgeries and procedures METHODS AND MATERIALS: Electronic search was conducted in PubMed, Scopus, Embase, Web of Science, ArXiv and Cochrane databases for the studies published until August 2022. Studies that reported the application of ML in various fields of facial cosmetic surgeries were included. The studies' risk of bias (ROB) was assessed using the QUADAS-2 tool and NIH tool for before and after studies.

RESULTS

From 848 studies, a total of 29 studies were included and categorized in five groups based on the aim of the studies: outcome evaluation (n = 8), face recognition (n = 7), outcome prediction (n = 7), patient concern evaluation (n = 4) and diagnosis (n = 3). Total of 16 studies used public data sets. ROB assessment using QUADAS-2 tool revealed that six studies were at low ROB, five studies were at high ROB, and others had moderate ROB. All studies assessed with NIH tool showed fair quality. In general, all studies showed that using ML in the facial cosmetic surgeries is accurate enough to benefit both surgeons and patients.

CONCLUSION

Using ML in the field of facial cosmetic surgery is a novel method and needs further studies, especially in the fields of diagnosis and treatment planning. Due to the small number of articles and the qualitative analysis conducted, we cannot draw a general conclusion about the impact of ML in the sphere of facial cosmetic surgery.

LEVEL OF EVIDENCE IV

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 for Analyzing the Contents of Social Media for Health Care: Scoping Review

BACKGROUND

Given the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews focus on the application of social media, and there is a lack of reviews that integrate the methods for analyzing social media information for health care.

OBJECTIVE

This scoping review aims to answer the following 4 questions: (1) What types of research have been used to investigate social media for health care, (2) what methods have been used to analyze the existing health information on social media, (3) what indicators should be applied to collect and evaluate the characteristics of methods for analyzing the contents of social media for health care, and (4) what are the current problems and development directions of methods used to analyze the contents of social media for health care?

METHODS

A scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted. We searched PubMed, the Web of Science, EMBASE, the Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library for the period from 2010 to May 2023 for primary studies focusing on social media and health care. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted.

RESULTS

Of 16,161 identified citations, 134 (0.8%) studies were included in this review. These included 67 (50.0%) qualitative designs, 43 (32.1%) quantitative designs, and 24 (17.9%) mixed methods designs. The applied research methods were classified based on the following aspects: (1) manual analysis methods (content analysis methodology, grounded theory, ethnography, classification analysis, thematic analysis, and scoring tables) and computer-aided analysis methods (latent Dirichlet allocation, support vector machine, probabilistic clustering, image analysis, topic modeling, sentiment analysis, and other natural language processing technologies), (2) categories of research contents, and (3) health care areas (health practice, health services, and health education).

CONCLUSIONS

Based on an extensive literature review, we investigated the methods for analyzing the contents of social media for health care to determine the main applications, differences, trends, and existing problems. We also discussed the implications for the future. Traditional content analysis is still the mainstream method for analyzing social media content, and future research may be combined with big data research. With the progress of computers, mobile phones, smartwatches, and other smart devices, social media information sources will become more diversified. Future research can combine new sources, such as pictures, videos, and physiological signals, with online social networking to adapt to the development trend of the internet. More medical information talents need to be trained in the future to better solve the problem of network information analysis. Overall, this scoping review can be useful for a large audience that includes researchers entering the field.

Evaluation of Post-Operative Patient Satisfaction and Rhinoplasty Decision Based on Pre-and PostOperative Images on Social Media

Objective: The novel objective of this research was to evaluate post-operative patient satisfaction among Turkish patients who decided to have rhinoplasty by seeing their pre-operative and post-operative images on social media. Method: This research compared and evaluated the collected data from three patient groups, namely Group 1, Group 2, and Group 3 to investigate the satisfaction level of the patients after the first year of the surgery. Result: The study found that the number of patients who decided to get rhinoplasty done after looking at images from social media were similar to other groups according to surgeon's scores. However, it was determined that the patient satisfaction of those who came after looking at images from social media was lower by a large margin and their expectations were not met by rhinoplasty. Conclusion: This research presented a novel theoretical implication that was not determined and evaluated by other studies in prior studies. The contribution of this research has reliable justification to improve patient satisfaction based on their health behavior to improve their level of satisfaction with rhinoplasty.

Applying Machine Learning to Determine Popular Patient Questions About Mentoplasty on Social Media

PURPOSE

Patient satisfaction in esthetic surgery often necessitates synergy between patient and physician goals. The authors aim to characterize patient questions before and after mentoplasty to reflect the patient perspective and enhance the physician-patient relationship.

METHODS

Mentoplasty reviews were gathered from Realself.com using an automated web crawler. Questions were defined as preoperative or postoperative. Each question was reviewed and characterized by the authors into general categories to best reflect the overall theme of the question. A machine learning approach was utilized to create a list of the most common patient questions, asked both preoperatively and postoperatively.

RESULTS

A total of 2,012 questions were collected. Of these, 1,708 (84.9%) and 304 (15.1%) preoperative and postoperative questions, respectively. The primary category for patients preoperatively was "eligibility for surgery" (86.3%), followed by "surgical techniques and logistics" (5.4%) and "cost" (5.4%). Of the postoperative questions, the most common questions were about "options to revise surgery" (44.1%), "symptoms after surgery" (27.0%), and "appearance" (26.3%). Our machine learning approach generated the 10 most common pre- and postoperative questions about mentoplasty. The majority of preoperative questions dealt with potential surgical indications, while most postoperative questions principally addressed appearance.

CONCLUSIONS

The majority of mentoplasty patient questions were preoperative and asked about eligibility of surgery. Our study also found a significant proportion of postoperative questions inquired about revision, suggesting a small but nontrivial subset of patients highly dissatisfied with their results. Our 10 most common preoperative and postoperative question handout can help better inform physicians about the patient perspective on mentoplasty throughout their surgical course. 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 .

Assessing Patient Satisfaction Following Blepharoplasty Using Social Media Reviews

BACKGROUND

Because patient satisfaction is a significant qualitative consideration in measuring aesthetic surgery outcome, it is important to characterize the individual factors that shape the patient perspective about blepharoplasty.

OBJECTIVES

This study analyzed reviews by blepharoplasty patients on the aesthetic surgery social media platform RealSelf.com to determine which aspects of the surgical process have the most significant impact on patient satisfaction.

METHODS

Blepharoplasty reviews were gathered from RealSelf.com with an automated web crawler. These reviews were characterized as positive or negative, then given a specific category that more specifically defined the theme of the review. Additional variables, including the specialty of the reviewed physician and any patient self-reported ratings, were documented.

RESULTS

A total of 1991 reviews pertaining to blepharoplasty were collected. Among reviews with self-reported "worth it" ratings, 93.5% were positive. Following categorization of all reviews, 1865 (93.7%) were positive and 126 (6.3%) were negative. Of the positive reviews, the most common overall themes were bedside manner (n = 899, 48.2%), aesthetic result (n = 859, 46.1%), and overall comfort (n = 58, 3.1%). Among negative reviews, most pertained to aesthetic result (n = 100, 79.4%), and bedside manner (n = 14, 11.1%). The most frequently encountered physician specialties performing blepharoplasty were plastic surgery (n = 1101, 55.3%), ophthalmology (n = 634, 31.8%), and otolaryngology (n = 69, 3.5%).

CONCLUSIONS

The majority of reviews were positive. The most prominent factor driving positive reviews was bedside manner, followed by aesthetic results. Negative reviews were most frequently attributed to suboptimal aesthetic results. Most blepharoplasties in our study cohort were performed by plastic and oculoplastic surgeons.