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1.
Healthcare (Basel) ; 11(10)2023 May 19.
Article in English | MEDLINE | ID: covidwho-20240493

ABSTRACT

Loneliness is an issue of public health significance. Longitudinal studies indicate that feelings of loneliness are prevalent and were exacerbated by the Coronavirus Disease 2019 (COVID-19) pandemic. With the advent of new media, more people are turning to social media platforms such as Twitter and Reddit as well as online forums, e.g., loneliness forums, to seek advice and solace regarding their health and well-being. The present study therefore aimed to investigate the public messaging on loneliness via an unsupervised machine learning analysis of posts made by organisations on Twitter. We specifically examined tweets put out by organisations (companies, agencies or common interest groups) as the public may view them as more credible information as opposed to individual opinions. A total of 68,345 unique tweets in English were posted by organisations on Twitter from 1 January 2012 to 1 September 2022. These tweets were extracted and analysed using unsupervised machine learning approaches. BERTopic, a topic modelling technique that leverages state-of-the-art natural language processing, was applied to generate interpretable topics around the public messaging of loneliness and highlight the key words in the topic descriptions. The topics and topic labels were then reviewed independently by all study investigators for thematic analysis. Four key themes were uncovered, namely, the experience of loneliness, people who experience loneliness, what exacerbates loneliness and what could alleviate loneliness. Notably, a significant proportion of the tweets centred on the impact of the COVID-19 pandemic on loneliness. While current online interactions are largely descriptive of the complex and multifaceted problem of loneliness, more targeted prosocial messaging appears to be lacking to combat the causes of loneliness brought up in public messaging.

2.
Antibiotics (Basel) ; 12(2)2023 Feb 18.
Article in English | MEDLINE | ID: covidwho-2243736

ABSTRACT

Pseudomonas aeruginosa (P. aeruginosa) is among the most common pathogens associated with healthcare-acquired infections, and is often antibiotic resistant, causing significant morbidity and mortality in cases of P. aeruginosa bacteremia. It remains unclear how the incidence of P. aeruginosa bacteremia changed during the Coronavirus Disease 2019 (COVID-19) pandemic, with studies showing almost contradictory conclusions despite enhanced infection control practices during the pandemic. This systematic review sought to examine published reports with incidence rates for P. aeruginosa bacteremia during (defined as from March 2020 onwards) and prior to the COVID-19 pandemic. A systematic literature search was conducted in accordance with PRISMA guidelines and performed in Cochrane, Embase, and Medline with combinations of the key words (pseudomonas aeruginosa OR PAE) AND (incidence OR surveillance), from database inception until 1 December 2022. Based on the pre-defined inclusion criteria, a total of eight studies were eligible for review. Prior to the pandemic, the prevalence of P. aeruginosa was on an uptrend. Several international reports found a slight increase in the incidence of P. aeruginosa bacteremia during the COVID-19 pandemic. These findings collectively highlight the continued importance of good infection prevention and control and antimicrobial stewardship during both pandemic and non-pandemic periods. It is important to implement effective infection prevention and control measures, including ensuring hand hygiene, stepping up environmental cleaning and disinfection efforts, and developing timely guidelines on the appropriate prescription of antibiotics.

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