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The need for feminist intersectionality in digital health.
Figueroa, Caroline A; Luo, Tiffany; Aguilera, Adrian; Lyles, Courtney R.
  • Figueroa CA; School of Social Welfare, University of California, Berkeley, CA, USA. Electronic address: c.a.figueroa@berkeley.edu.
  • Luo T; School of Social Welfare, University of California, Berkeley, CA, USA.
  • Aguilera A; School of Social Welfare, University of California, Berkeley, CA, USA; Zuckerberg San Francisco General Hospital, UCSF, San Francisco, CA, USA.
  • Lyles CR; Department of Medicine and Department of Epidemiology and Biostatistics and UCSF Center for Vulnerable Populations at Zuckerberg San Francisco General Hospital, UCSF, San Francisco, CA, USA.
Lancet Digit Health ; 3(8): e526-e533, 2021 08.
Article in English | MEDLINE | ID: covidwho-1333841
ABSTRACT
Digital health, including the use of mobile health apps, telemedicine, and data analytics to improve health systems, has surged during the COVID-19 pandemic. The social and economic fallout from COVID-19 has further exacerbated gender inequities, through increased domestic violence against women, soaring unemployment rates in women, and increased unpaid familial care taken up by women-all factors that can worsen women's health. Digital health can bolster gender equity through increased access to health care, empowerment of one's own health data, and reduced burden of unpaid care work. Yet, digital health is rarely designed from a gender equity perspective. In this Viewpoint, we show that because of lower access and exclusion from app design, gender imbalance in digital health leadership, and harmful gender stereotypes, digital health is disadvantaging women-especially women with racial or ethnic minority backgrounds. Tackling digital health's gender inequities is more crucial than ever. We explain our feminist intersectionality framework to tackle digital health's gender inequities and provide recommendations for future research.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Ethnicity / Women's Health / Telemedicine / Feminism / Sexism / Minority Groups Type of study: Randomized controlled trials Limits: Female / Humans Language: English Journal: Lancet Digit Health Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Ethnicity / Women's Health / Telemedicine / Feminism / Sexism / Minority Groups Type of study: Randomized controlled trials Limits: Female / Humans Language: English Journal: Lancet Digit Health Year: 2021 Document Type: Article