scholarly journals Social Media Content of Idiopathic Pulmonary Fibrosis Groups and Pages on Facebook: A Cross Sectional Analysis (Preprint)

2020 ◽  
Author(s):  
Andrew Kochan ◽  
Shaun Ong ◽  
Sabina Guler ◽  
Kerri A. Johannson ◽  
Christopher J. Ryerson ◽  
...  

BACKGROUND Patients use Facebook as a resource for medical information. We analyzed posts on idiopathic pulmonary fibrosis (IPF)-related Facebook groups and pages for presence of guideline content, user engagement, and usefulness. OBJECTIVE The objective of this study was to describe and analyze posts from Facebook groups and pages that primarily focus on IPF-related content. METHODS Cross-sectional analysis was performed on a single date, identifying Facebook groups and pages resulting from separately searching “IPF” and “idiopathic pulmonary fibrosis”. For inclusion, groups and pages needed to meet either search term and be in English, publicly available, and relevant to IPF. Every tenth post was assessed for general characteristics, source, focus, and user engagement metrics. Posts were analyzed for presence of IPF guideline content, useful scientific information (e.g. scientific publications), useful support information (e.g. information about support groups), and potentially harmful information. RESULTS Eligibility criteria were met by 12 groups and 27 pages, leading to analysis of 523 posts. Of these, 42% contained guideline content, 24% provided useful support, 20% provided useful scientific information, and 5% contained potentially harmful information. Post source was most commonly non-medical users (85%). Posts most frequently focused on IPF-related news (29%). Posts containing any guideline content had fewer likes or comments and a higher likelihood of containing potentially harmful content. Posts containing useful supportive information had more likes, shares, and comments. CONCLUSIONS Facebook contains useful information about IPF, but posts with misinformation and less guideline content have higher user engagement, making them more visible. Identifying ways to help IPF patients discriminate between useful and harmful information on Facebook and other social media platforms is an important task for healthcare professionals.

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Donato Lacedonia ◽  
Giulia Scioscia ◽  
Piera Soccio ◽  
Massimo Conese ◽  
Lucia Catucci ◽  
...  

Abstract Background Idiopathic Pulmonary Fibrosis (IPF) is a degenerative interstitial lung disease with both a poor prognosis and quality of life once the diagnosis is made. In the last decade many features of the disease have been investigated to better understand the pathological steps that lead to the onset of the disease and, moreover, different types of biomarkers have been tested to find valid diagnostic, prognostic and therapy response predictive ones. In the complexity of IPF, microRNA (miRNAs) biomarker investigation seems to be promising. Methods We analysed the expression of five exosomal miRNAs supposed to have a role in the pathogenesis of the disease from serum of a group of IPF patients (n = 61) and we compared it with the expression of the same miRNAs in a group of healthy controls (n = 15). Results In the current study what emerged is let-7d down-regulation and, unexpectedly, miR-16 significant down-regulation. Moreover, through a cross-sectional analysis, a clustering of the expression of miR-16, miR-21 and miR-26a was found. Conclusions These findings could help the individuation of previously unknown key players in the pathophysiology of IPF and, most interestingly, more specific targets for the development of effective medications.


2017 ◽  
Author(s):  
Justin D Triemstra ◽  
Rachel Stork Poeppelman ◽  
Vineet M Arora

BACKGROUND The US News and World Report reputation score correlates strongly with overall rank in adult and pediatric hospital rankings. Social media affects how information is disseminated to physicians and is used by hospitals as a marketing tool to recruit patients. It is unclear whether the reputation score for adult and children’s hospitals relates to social media presence. OBJECTIVE The objective of our study was to analyze the association between a hospital’s social media metrics and the US News 2017-2018 Best Hospital Rankings for adult and children’s hospitals. METHODS We conducted a cross-sectional analysis of the reputation score, total score, and social media metrics (Twitter, Facebook, and Instagram) of hospitals who received at least one subspecialty ranking in the 2017-2018 US News publicly available annual rankings. Regression analysis was employed to analyze the partial correlation coefficients between social media metrics and a hospital’s total points (ie, rank) and reputation score for both adult and children’s hospitals while controlling for the bed size and time on Twitter. RESULTS We observed significant correlations for children’s hospitals’ reputation score and total points with the number of Twitter followers (total points: r=.465, P<.001; reputation: r=.524, P<.001) and Facebook followers (total points: r=.392, P=.002; reputation: r=.518, P<.001). Significant correlations for the adult hospitals reputation score were found with the number of Twitter followers (r=.848, P<.001), number of tweets (r=.535, P<.001), Klout score (r=.242, P=.02), and Facebook followers (r=.743, P<.001). In addition, significant correlations for adult hospitals total points were found with Twitter followers (r=.548, P<.001), number of tweets (r=.358, P<.001), Klout score (r=.203, P=.05), Facebook followers (r=.500, P<.001), and Instagram followers (r=.692, P<.001). CONCLUSIONS A statistically significant correlation exists between multiple social media metrics and both a hospital’s reputation score and total points (ie, overall rank). This association may indicate that a hospital’s reputation may be influenced by its social media presence or that the reputation or rank of a hospital drives social media followers.


10.2196/26134 ◽  
2020 ◽  
Author(s):  
Lauren A. Rutter ◽  
Holly M. Thompson ◽  
Jacqueline Howard ◽  
Tennisha N. Riley ◽  
Robinson De Jesús-Romero ◽  
...  

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