ArticleAmpersand (Oxford, UK)2023
World Health Organization myth busters and indigenous perceptions of COVID-19: Quechua and Shipibo communities.
Article in Ampersand (Oxford, UK), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Lessons from community engagement to improve COVID-19 diagnosis and treatment in Cochabamba, Bolivia.Global health action · 2024Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
When the COVID (SARS-V2) pandemic swept across the world, it impacted Indigenous communities more than others. This is due to a variety of reasons: socioeconomic injustice and racialization, lack of access to equitable healthcare, and linguistic discrimination. As a result, several communities and community types demonstrated this effect when perceptions of inferences or other COVID-related information were measured. This paper reports on a participatory collaborative study with two Indigenous communities in rural Peru-ten Quechua-speaking communities in Southern Cuzco and three Shipibo-speaking communities in Ucayali regions. We investigate the communities' level of preparedness for the crisis by eliciting answers based on the World Health Organization COVID 'MythBusters' in a form of a semi-structured interview. Interviews were transcribed, translated, and analyzed in search of the effect of three variables: gender (male/female), language group (Shipibo/Quechua), and proficiency in the Indigenous language (from 0 to 4). Data reveal that all three variables have some effect on the target comprehension of COVID-related messages. Additionally, we explore other possible explanations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.