| Title: |
Community-Engaged Survey Approach to Pandemic Impacts on Marginalized Communities, Massachusetts, 2020–2021. |
| Authors: |
Cardoso, Lauren F.; Lin, Ta-wei; Egan, Justine; Stack, Caroline; Selk, Sabrina; Beatriz, Elizabeth; Wood, Ben; Song, Glory; Fitzsimmons, Kathleen; Sparer-Fine, Emily; Atkins, Abigail; Ursprung, W.W. Sanouri |
| Source: |
American Journal of Public Health; 2024 Suppl 7, Vol. 114, pS599-S609, 11p |
| Subject Terms: |
Health services accessibility; Cross-sectional method; Community support; Parents; Research funding; Mental health; Asian Americans; At-risk people; Investments; Work environment; Communities; Surveys; Health planning; Pacific Islander Americans; Health equity; Discrimination (Sociology); COVID-19 pandemic; Patients' attitudes; Patient participation; Industrial safety; Employment |
| Geographic Terms: |
Massachusetts |
| Abstract: |
Objectives. To describe how an innovative, community-engaged survey illuminated previously unmeasured pandemic inequities and informed health equity investments. Methods. The methodological approach of Massachusetts' COVID-19 Community Impact Survey, a cross-sectional online survey, was driven by key health equity principles: prioritizing community engagement, gathering granular and intersectional data, capturing root causes, elevating community voices, expediting analysis for timeliness, and creating data-to-action pathways. Data collection was deployed statewide in 11 languages from 2020 to 2021. Results. The embedded equity principles resulted in a rich data set and enabled analyses of populations previously undescribed. The final sample included 33 800 respondents including unprecedented numbers of populations underrepresented in traditional data sources. Analyses indicated that pandemic impacts related to basic needs, discrimination, health care access, workplace protections, employment, and mental health disproportionately affected these priority populations, which included Asian American/Pacific Islanders and parents. Conclusions. Equity-centered data approaches allow for analyses of populations previously invisible in surveillance data, enable more equitable public health action, and are both possible and necessary to deploy in state health departments. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |