Gender as a social and structural variable: research perspectives from the National Institutes of Health (NIH).

Gender is a social and structural variable that encompasses multiple domains, each of which influences health: gender identity and expression, gender roles and norms, gendered power relations, and gender equality and equity. As such, gender has far-reaching impacts on health. Additional research is needed to continue delineating and untangling the effects of gender from the effects of sex and other biological variables. The National Institutes of Health (NIH) vision for women's health is a world in which the influence of sex and/or gender are integrated into the health research enterprise. However, much of the NIH-supported research on gender and health has, to date, been limited to a small number of conditions (e.g., HIV, mental health, pregnancy) and locations (e.g., sub-Saharan Africa; India). Opportunities exist to support transdisciplinary knowledge transfer and interdisciplinary knowledge building by advancing health-related social science research that incorporates best practices from disciplines that have well-established methods, theories, and frameworks for examining the health impacts of gender and other social, cultural, and structural variables.

Gender encompasses multiple domains, each of which influences health: identity and expression; roles and norms; relations; and power. This commentary focuses on gender-related research at the National Institutes of Health (NIH); identifies areas of opportunity for future health research efforts on gender; and articulates a vision for the robust, transdisciplinary incorporation of gender as a social, cultural, and structural variable into the NIH research agenda. The NIH vision for women's health is a world in which the influence of sex and/or gender are integrated into the health research enterprise. However, much of the NIH-supported research on gender and health has, to date, been limited to a small number of conditions (e.g., HIV, mental health, pregnancy) and locations (e.g., sub-Saharan Africa; India). Approaching the influences of gender on health with scientific rigor is critical to advancing health research that promotes health equity.

Advancing digital health equity: Directions for behavioral and social science research.

The field of digital health is evolving rapidly and encompasses a wide range of complex and changing technologies used to support individual and population health. The COVID-19 pandemic has augmented digital health expansion and significantly changed how digital health technologies are used. To ensure that these technologies do not create or exacerbate existing health disparities, a multi-pronged and comprehensive research approach is needed. In this commentary, we outline five recommendations for behavioral and social science researchers that are critical to promoting digital health equity. These recommendations include: (i) centering equity in research teams and theoretical approaches, (ii) focusing on issues of digital health literacy and engagement, (iii) using methods that elevate perspectives and needs of underserved populations, (iv) ensuring ethical approaches for collecting and using digital health data, and (v) developing strategies for integrating digital health tools within and across systems and settings. Taken together, these recommendations can help advance the science of digital health equity and justice.

The field of digital health is quickly growing and changing. Digital health technologies have the potential to increase access to health-related information and healthcare and improve wellbeing, but it is important that those technologies don't widen existing health disparities or create new ones. Behavioral and social science researchers have a key role to play in centering equity in their research teams and theoretical approaches, focusing on key barriers to access, uptake, and usage, studying digital health in ways that elevate the voices and needs of historically underserved groups, being thoughtful about how digital health data are collected and used, and making sure that digital health tools are designed to be used in real-world settings.