The field of research evaluation and integrity is moving towards a more nuanced understanding of the complex factors that influence the validity and reliability of scientific findings. Recent studies have highlighted the importance of considering the social and cultural context in which research is conducted and disseminated. The use of advanced methodologies, such as machine learning and natural language processing, is becoming increasingly prevalent in the analysis of large datasets and the identification of patterns and trends. Furthermore, there is a growing recognition of the need for greater transparency and accountability in the research process, including the use of open access publishing and the disclosure of conflicts of interest. Noteworthy papers include: The study on news and social media attention reducing the influence of problematic research, which found that high levels of news and social media attention can accelerate the retraction process and increase the visibility of retracted articles. The introduction of the h-leadership index, a novel variant of the h-index that gives importance to authorship position beyond the first and last authors, providing a more balanced assessment of research performance.