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Neglected tropical diseases affect more than a billion people worldwide, cause ill health and perpetuate cycles of poverty. Behavioural change can help, particularly through hygiene. But to achieve this we first need to understand the complex circumstances that mean hygiene is not always prioritized.
The Global Flourishing Study is a longitudinal panel study that is collecting nationally representative, multidimensional well-being data from more than 200,000 people in 22 geographically and culturally diverse countries. The first wave of results highlights the value of tracking a rich set of flourishing indicators for both science and policy.
Postnatal brain development is important for individual and societal outcomes. We need large-scale cohort studies from diverse populations to generate generalizable insights into the factors that affect children’s brain development. Here we discuss the contribution of the Chinese Child Brain Development project.
Large language models (LLMs) can enhance experimental research via the design and implementation of studies, and data analysis. When available, we suggest using LLM-based tools that require no coding skills and only a simple human–AI interaction. We discuss the social risks associated with this integration.
In the month of International Women’s Day, we asked six scientists about the most influential woman who shaped their field. They highlight well-known names and rising stars. Some of them have studied gender equality, and all have made tremendous efforts towards achieving it.
Mobility data can help to reconstruct infectious disease dynamics and tailor control and elimination measures. We describe three challenges and opportunities to improve our understanding of human mobility for infectious disease research. We call for simulation and modelling, reporting guidelines and investment in data repositories.
Psychology is fragmented into the study of a myriad of constructs and measures, most of which are used very rarely. This hinders cumulative knowledge generation. We call on the field to defragment psychology and prevent further fragmentation. We provide four key recommendations to achieve this and summarize the needed actions.
In this Comment, Emily Jones discusses what we can learn from archaeology about climate change resilience. The effects of climate change are complex, and successful adaptations in the past responded to local conditions. This suggests that collaborative, place-based research is key to resilience to future climate change.
Diversity, equity and inclusion (DEI) initiatives do not always translate across different contexts. Hye Yun Kang highlights the complexities of implementing DEI policies across cultures.
Understanding when and why laypeople adopt predictive algorithms is key to aligning technology with user needs. I propose that adoption is driven by performance expectations (as algorithms are tools designed to aid users) and outline when laypeople are likely to adopt algorithms, given their distinctive performance goals.
The growth of artificial intelligence (AI) in Africa faces a key challenge: a lack of quality data. This Comment explores datasets in agriculture, health and energy, and advocates for Afrocentric data that reflect African experiences.
In the USA, the Trump administration has signed executive orders that impose censorship on key areas of scientific research, strip government scientists of their jobs and reduce federal funding for science. Five co-organizers of the nationwide Stand Up For Science movement explain the need for collective action at this time.
Scientific publications often benefit from diverse contributions that go uncredited owing to a lack of guidelines for recognizing non-author contributors. We propose ‘extended research credits’ — a standardized, tiered system (modelled after the attribution style of the film industry) to highlight hidden labour in research.
Most empirical research articles feature a single primary analysis that is conducted by the authors. However, different analysis teams usually adopt different analytical approaches and frequently reach varied conclusions. We propose synchronous robustness reports — brief reports that summarize the results of alternative analyses by independent experts — to strengthen the credibility of science.
The integration of generative artificial intelligence (AI) and large language models (LLMs) in academia brings benefits for access and collaboration as well as challenges that include misinformation and threats to academic integrity. We examine 80 academic guidelines and recommend balanced approaches for the responsible integration of generative AI and LLMs in education.
Academia is not a welcoming place for women who want both a family and a career. Natalia Ocampo-Peñuela draws on her own experience to explain how this must change.
