USC digital health database to eliminate ‘one-size-fits-all’ approach by focusing on marginalized group representation

The Los Angeles-based USC Schaeffer Center for Health Policy & & Economics is developing a digital health dataset intended at successfully representing marginalized groups in medical research study.

The research group will offer individuals with Fitbit gadgets to track their physical activity, heart rate and sleep, as well as evaluate month-to-month study data. The task will oversample from marginalized groups, since a lot of existing datasets are biased due to not collecting an individual body that precisely reflects the nations demographic makeup.

The project, called American Life in Real-time, will employ digital innovations to better comprehend the medical and social needs of underrepresented groups, which will cultivate the advancement of equitable public health initiatives..

Katie Adams –
Wednesday, July 29th, 2020
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” Current research study is restricted by a lack of complete and representative datasets. Our objective is to alter this and ultimately better comprehend how different populations have various health habits and experience different social factors of health,” Ritika Chaturvedi, PhD, the tasks primary investigator, said in a July 28 news release. “With that details we hope to develop precision public health interventions that meet individual needs, instead of depending on our existing one-size-fits-all technique.”.

American Life in Real-time is funded by a four-year, $1.2 million grant from the National Institutes of Health.

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” Current research study is limited by a lack of total and representative datasets. Our goal is to change this and eventually better comprehend how different populations have various health behaviors and experience various social factors of health,” Ritika Chaturvedi, PhD, the jobs principal private investigator, said in a July 28 news release. “With that details we hope to create accuracy public health interventions that meet specific requirements, rather than relying on our existing one-size-fits-all approach.”.