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Background: With the increasing popularity of web 2.0 apps, social media has made it possible for individuals to post messages on antibiotic ineffectiveness. In such online conversations, patients discuss their quality of life (QoL). Social media have become key tools for finding and disseminating medical information.
Objective: To identify the main themes of discussion, the difficulties encountered by patients with respect to antibiotic ineffectiveness and the impact on their QoL (physical, psychological, social, or financial).
Methods: A noninterventional retrospective study was carried out by collecting social media posts in French language written by internet users mentioning their experience with antibiotics, and the impact of their ineffectiveness on their QoL. Messages posted between January 2014 and July 2020 were extracted from French-speaking publicly available online forums.
Results: A total of 3773 messages were included in the analysis corpus after extraction and filtering. These messages were posted by 2335 individual web users, most of them being women around 35 years of age. Inefficacy of treatment options and the lack of information regarding the use of antibiotics were among the most discussed topics. QoL was discussed in 63% of the 3773 messages posted. The most common is the physical impact (78%). Patients discussed the persistence of symptoms and adverse effects. The second kind of impact is psychological (65%), characterized by feelings of anxiety or despair about the situation.
Conclusions: This social media analysis allowed us to identify a strong impact of the perceived ineffectiveness of antibiotic therapy on patients' daily life particularly in terms of physical and psychological consequences. These results provide health care experts information directly generated by patients regarding their own experiences. Social media studies constitute a complementary source of evidence that could be used to optimize messages to the public about appropriate use of antibiotics.
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http://dx.doi.org/10.2196/37160 | DOI Listing |
Hernia
September 2025
Center for Perioperative Optimization, Department of Surgery, Copenhagen University Hospital - Herlev and Gentofte, Borgmester Ib Juuls Vej 1, Herlev, DK-2730, Denmark.
Purpose: Primary ventral hernia repair is a common elective procedure; however, mesh placement practices vary widely, and there is limited evidence to guide optimal placement. This international study examined surgeons' preferences and considerations regarding mesh placement in elective primary ventral hernia repair.
Methods: We conducted an international cross-sectional survey targeting surgeons experienced in primary ventral hernia repair.
Climacteric
September 2025
Gynecology Discipline, Obstetrics and Gynecology Department, University of São Paulo School of Medicine, São Paulo, Brazil.
Objective: Social media is an increasingly relevant tool for health education, enabling information exchange, promoting autonomy and supporting informed decision-making. This study introduces Menopausando, a predominantly Portuguese-language digital platform designed to support women during menopausal transition and postmenopause.
Method: This cross-sectional study has been carried out in the Gynecology Discipline, São Paulo University, Brazil, since 2019.
JTCVS Open
August 2025
Department of Cardiothoracic Surgery, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Background: Social media use among cardiothoracic surgeons has yet to be analyzed. This study aimed to explore how online media utilization by cardiothoracic surgeons differs by subspecialty, sex, geographic region, practice type, level of experience, and training pathway.
Methods: A list of 223 cardiothoracic surgeons was generated by querying the 1066 members of the American Association for Thoracic Surgery and randomly selecting 223 actively practicing surgeons.
Health Inf Sci Syst
December 2025
Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000 China.
Leveraging natural language processing to identify anxiety states from social media has been widely studied. However, existing research lacks deep user-level semantic modeling and effective anxiety feature extraction. Additionally, the absence of clinical domain knowledge in current models limits their interpretability and medical relevance.
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