Sex and gender differences impact the incidence of SARS-CoV-2 infection and COVID-19 mortality. Furthermore, sex differences influence the frequency and severity of pharmacological side effects. A large number of clinical trials to develop new therapeutic approaches and vaccines for COVID-19 are ongoing. We investigated the inclusion of sex and/or gender in COVID-19 studies on ClinicalTrials.gov, collecting data for the period January 1, 2020 to January 26, 2021. Here, we show that of the 4,420 registered SARS-CoV-2/COVID-19 studies, 935 (21.2%) address sex/gender solely in the context of recruitment, 237 (5.4%) plan sex-matched or representative samples or emphasized sex/gender reporting, and only 178 (4%) explicitly report a plan to include sex/gender as an analytical variable. Just eight (17.8%) of the 45 COVID-19 related clinical trials published in scientific journals until December 15, 2020 report sex-disaggregated results or subgroup analyses.

Sex and gender differences impact the incidence of SARS-CoV-2 infection and COVID-19 mortality. Furthermore, sex differences characterize the frequency and severity of pharmacological side effects. A large number of clinical trials are ongoing to develop new therapeutic approaches and vaccines for COVID-19. We investigated the inclusion of sex and/or gender in currently registered studies on ClinicalTrials.gov. Only 416 (16.7%) of the 2,484 registered SARS-CoV-2/COVID-19 trials mention sex/gender as recruitment criterion and only 103 (4.1%) allude to sex/gender in the description of the analysis phase. None of the 11 clinical trials published in scientific journals on June 2020 reported sex-disaggregated results. Hence, lack of consideration upon registration does not seem to be corrected during trial execution and reporting. Given the biological relevance and the potential risks of unwanted side effects, we urge researchers to focus on sex-disaggregated analyses already at the planning stage of COVID-19 trials.

Background In recent years, interest has grown in whether and to what extent demographic diversity sparks discovery and innovation in research. At the same time, topic modeling has been employed to discover differences in what women and men write about. This study engages these two strands of scholarship to explore associations between changing researcher demographics and research questions asked in the discipline of history. Specifically, we analyze developments in history as women entered the field. Methods We focus on author gender in diachronic analysis of history dissertations from 1980 (when online data is first available) to 2015 and a select set of general history journals from 1950 to 2015. We use correlated topic modeling and network visualizations to map developments in research agendas over time and to examine how women and men have contributed to these developments. Results Our summary snapshot of aggregate interests of women and men for the period 1950 to 2015 identifies new topics associated with women authors: gender and women’s history, body history, family and households, consumption and consumerism, and sexuality. Diachronic analysis demonstrates that while women pioneered topics such as gender and women’s history or the history of sexuality, these topics broaden over time to become methodological frameworks that historians widely embraced and that changed in interesting ways as men engaged with them. Our analysis of history dissertations surface correlations between advisor/advisee gender pairings and choice of dissertation topic. Conclusions Overall, this quantitative longitudinal study suggests that the growth in women historians has coincided with the broadening of research agendas and an increased sensitivity to new topics and methodologies in the field.

Research suggests that scientists based at prestigious institutions receive more credit for their work than scientists based at less prestigious institutions, as do scientists working in certain countries. We examined the extent to which country- and institution-related status signals drive such differences in scientific recognition. In a preregistered survey experiment, we asked 4,147 scientists from six disciplines (astronomy, cardiology materials science, political science, psychology and public health) to rate abstracts that varied on two factors: i) author country (high status vs lower status in science); ii) author institution (high status vs lower status university). We found only weak evidence of country- or institution-related status bias, and mixed regression models with discipline as random-effect parameter indicated that any plausible bias not detected by our study must be small in size.

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