Long covid (persistent COVID-19) is a new disease with contested aetiology and variable prognosis. We report a 2-year ethnography of UK long covid clinics. Using a preformative lens, we show that multidisciplinary teams (MDTs) built working knowledge based on shared practices, mutual trust, distributed cognition (e.g. emails, record entries), relational knowledge of what was at stake for the patient, and harnessing uncertainty to open new discursive spaces. Most long covid MDTs performed the working knowledge of 'rehabilitation', a linked set of practices oriented to ensuring that the patient understood and strove to 'correct' maladaptive physiological responses (e.g. through breathing exercises) and pursued recovery goals, supported by physiotherapists, psychologists and generalist clinicians. Some MDTs with a higher proportion of doctors (e.g. cardiologists, neurologists, immunologists) enacted the working knowledge of 'microscopic damage', seeking to elucidate and rectify long covid's underlying molecular and cellular pathology. They justified non-standard investigations and medication in selected patients by co-constructing an evidentiary narrative based on biological mechanisms. Working knowledge was ontologically concordant within MDTs but sometimes discordant between MDTs. Overt ontological conflict occurred mostly when patients attending 'rehabilitation' clinics invoked the working knowledge of microscopic damage that had been generated and circulated in online support communities.
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http://dx.doi.org/10.1111/1467-9566.13819 | DOI Listing |
The history of the Croatian pharmaceutical company PLIVA from the very beginning to the status of a recognisable European and global player is described. Special attention is paid to PLIVA's cooperation with the Croatian Nobel laureate Vladimir Prelog and the invention of the proprietary antibiotic azithromycin. The antibiotic was commercialised in cooperation with the US-based company Pfizer.
View Article and Find Full Text PDFJ Gen Intern Med
January 2025
Department of Medicine and Population Health, Institute for Excellence in Health Equity, New York University Grossman School of Medicine, New York, NY, USA.
The Journal of General Internal Medicine (JGIM) has a long-standing history of publishing manuscripts focused on health equity and is committed to diversity, equity, and inclusion (DEI) in scientific writing and publishing. This is extremely important in the current climate where false narratives and attacks on DEI and health equity are rampant. To demonstrate their commitment to DEI and health equity, the JGIM Editors-in-Chief created an inaugural DEI Advocacy Team.
View Article and Find Full Text PDFJ Relig Health
January 2025
School of Social Work, Hadassah Academic College, Jerusalem, Israel.
Religious informal helpers may play a crucial role in recognizing and providing referrals to mental health professional for at-risk individuals, including those with mental illness, especially since members of religious communities tend to conceal their difficulties and to view religious leaders as a sole source of assistance. This quantitative study aimed to explore Jewish bathhouse attendants ("balaniyot") who assist women in their monthly immersion, a unique situation in which mental health symptoms (e.g.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Hematology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, 445000, China.
A study in the Enshi Region between Sept-Nov 2023 assessed medical staff's knowledge, attitude, and practice regarding multiple myeloma. The disease significantly impacts physical health, quality of life, and mental well-being. Medical professionals play crucial roles in its prevention and treatment.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Computer Science, College of Computer and Information Sciences, King Saud University, 11543, Riyadh, Saudi Arabia.
Understanding the nuanced emotions and points of view included in user-generated content remains challenging, even though text data analysis for mental health is a crucial instrument for assessing emotional well-being. Most current models neglect the significance of integrating viewpoints in comprehending mental health in favor of single-task learning. To offer a more thorough knowledge of mental health, in this study, we present an Opinion-Enhanced Hybrid BERT Model (Opinion-BERT), built to handle multi-task learning for simultaneous sentiment and status categorization.
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