About The Study: Stratified analyses in this study revealed that prediabetes was significantly associated with mortality only among younger adults (ages 20-54), highlighting the importance of age-specific interventions. Lifestyle behaviors, limited health care access, and life stage challenges may contribute to the increased mortality risk in younger adults. Early-onset health problems in this group may also reflect stronger genetic predispositions, leading to more rapid disease progression and more severe health outcomes. These findings underscore the need for tailored diabetes prevention programs targeting young adults—such as flexible, virtual, and peer-led options—to increase accessibility and engagement. Routine screening and timely referrals to age-appropriate programs are essential.

The first paper from a multi-year clinical research study has been published in The Lancet Infectious Diseases: Dynamics of Endemic Virus Re-emergence in Children in the USA Following the COVID-19 Pandemic (2022-2023): A Longitudinal Immunoepidemiologic Surveillance Study and demonstrates how the approach can improve modeling to better predict future outbreaks.

The paper shares findings from a multicenter clinical research study, one of many studies that are part of the recently launched PREMISE (Pandemic Response Repository through Microbial and Immune Surveillance and Epidemiology) program, led by Dr. Daniel Douek at the National Institutes of Health’s (NIH) Vaccine Research Center (VRC). Data collected during the first year of the PREMISE study, 2022-2023, shows for the first time how non-pharmaceutical interventions such as masking and distancing targeted towards SARS-CoV-2 during the pandemic also decreased circulation rates of and population immunity to common respiratory pathogens in children. The study provides new evidence-based insight into what was driving the large post-pandemic rebound in these diseases and enables more accurate predictions for the future.

Large language models such as ChatGPT recognise widespread myths about the human brain better than many educators. However, if false assumptions are embedded into a lesson scenario, artificial intelligence (AI) does not reliably correct them. These were the findings of an international study that included psychologists from Martin Luther University Halle-Wittenberg (MLU). The researchers attribute this behaviour to the fundamental nature of AI models: they act as people pleasers. However, this problem can be solved by a simple trick. The study was published in the journal “Trends in Neuroscience and Education”.

Researchers from the HSE Laboratory for Cognitive Psychology of Digital Interface Users have discovered how social cues in the design of news websites—such as reader comments, the number of reposts, or the author’s name—can help build user trust. An experiment with 137 volunteers showed that such interface elements make a website appear more trustworthy and persuasive to users, with the strongest cue being links to social media pages. The study's findings have been published in Human-Computer Interaction.