RESUMO
This study seeks to identify and characterize key barriers associated with PrEP therapy as self-reported by users on social media platforms. We used data mining and unsupervised machine learning approaches to collect and analyze COVID-19 and PrEP-related posts from three social media platforms including Twitter, Reddit, and Instagram. Predominant themes detected by unsupervised machine learning and manual annotation included users expressing uncertainty about PrEP treatment adherence due to COVID-19, challenges related to accessibility of clinics, concerns about PrEP costs and insurance coverage, perceived lower HIV risk leading to lack of adherence, and misinformation about PrEP use for COVID-19 prevention.
Assuntos
COVID-19 , Infecções por HIV , Conhecimentos, Atitudes e Prática em Saúde , Acessibilidade aos Serviços de Saúde , Infodemiologia , Profilaxia Pré-Exposição , Mídias Sociais , COVID-19/epidemiologia , COVID-19/prevenção & controle , Infecções por HIV/economia , Infecções por HIV/prevenção & controle , Infecções por HIV/psicologia , Humanos , Autorrelato , Aprendizado de Máquina não Supervisionado , Mineração de Dados , Incerteza , Cobertura do Seguro , Grupos Minoritários , PandemiasRESUMO
Race, ethnicity, sex, and age are demographic factors that can influence drug exposure and/or response, and can consequently affect treatment outcome. We evaluated demographic subgroup enrollment patterns in new therapeutic products approved by the US Food and Drug Administration (FDA) for the treatment of select cancers-breast, colorectal, lung, and prostate-that have comparative differences in morbidity and/or mortality among some demographic subgroups. In submissions of products approved between 2008 and 2013, participants (n = 22,481) were white (80%), from outside the United States (74%), between 17 and 64 years old (59%), and men (56% and 53%, including and excluding sex-specific indications, respectively). In pivotal trials of products approved between2014 and 2017, participants (n = 3,612) were white (71%), between 17 and 64 years old (61%), and men (48% and 63%, including and excluding sex-specific indications, respectively). The US-relevant minority populations were under-represented. A broader representation of patient subgroups in clinical trials may contribute to better understanding of exposure and/or response variability, and consequently help personalize drug therapy.