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This article examines UK newspaper coverage during the first wave of the COVID-19 pandemic March-August 2020. A qualitative framing analysis of public messaging on age in five high circulation newspapers provides a detailed account of who is deemed to be at risk of dying from COVID-19. Newspapers represent older people as most at risk, with disability as a secondary factor. Reports on who is responsible, who is at risk, and who is to blame for deaths from COVID-19 are framed as issues of public health and generational fairness, with individual responsibility occupying a prominent role. We also find two counter-frames. First, in letters to the editor, older people's pleas for freedom are framed as a fight for their civil liberties. Second, newspapers praise 99-year-old Captain Tom Moore and frame his behaviour as a source of national pride. We identify this as positive ageism. We conclude that reporting across progressive and conservative newspapers reflects age-based stereotypes and paternalism towards older people. Public figures are represented as scapegoats or heroes, offering distraction from the less newsworthy fact that long-term under-investment in social care increased the risk of dying amongst the old and disabled during the pandemic. [ABSTRACT FROM AUTHOR]

Flashbulb memories (FBMs) refer to vivid and long-lasting autobiographical memories for the circumstances in which people learned of a shocking and consequential public event. A cross-national study across eleven countries aimed to investigate FBM formation following the first COVID-19 case news in each country and test the effect of pandemic-related variables on FBM. Participants had detailed memories of the date and others present when they heard the news, and had partially detailed memories of the place, activity, and news source. China had the highest FBM specificity. All countries considered the COVID-19 emergency as highly significant at both the individual and global level. The Classification and Regression Tree Analysis revealed that FBM specificity might be influenced by participants' age, subjective severity (assessment of COVID-19 impact in each country and relative to others), residing in an area with stringent COVID-19 protection measures, and expecting the pandemic effects. Hierarchical regression models demonstrated that age and subjective severity negatively predicted FBM specificity, whereas sex, pandemic impact expectedness, and rehearsal showed positive associations in the total sample. Subjective severity negatively affected FBM specificity in Turkey, whereas pandemic impact expectedness positively influenced FBM specificity in China and negatively in Denmark. [ABSTRACT FROM AUTHOR]

"Black Handsworth: Race in 1980s Britain" by Kieran Connell is a valuable contribution to the study of Britain's post-war black population. The book explores the Handsworth district of Birmingham during the 1980s, focusing on the political organizations, visual productions, Rastafarianism, and everyday life of the Afro-Caribbean community. Connell's use of diverse sources, including archives, photography, film, music, and oral history, provides a comprehensive understanding of black life in Handsworth. While the book lacks some contextual information and contains minor factual inaccuracies, it is still highly recommended for researchers and students interested in black British history and post-war British history. [Extracted from the article]

The article stresses the need to reflect carefully upon what people read. Topics discussed include possible effects of the apparent negative bias or emphasis on unusual events, reasons that popular misconceptions arise according to epidemiologist Hans Rosling, and importance of understanding the extent of publication bias according to R. C. M. van Aert and colleagues.

Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS. Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status. DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them. [ABSTRACT FROM AUTHOR]