Advancing Healthcare for COVID-19 by Strengthening Providers’ Capacity for Best Practices in African, Caribbean and Black Community Service Provision in Ontario: A Multisite Mixed-Method Study Protocol

Autor: Josephine Etowa, LaRon Nelson, Egbe Etowa, Getachew Abrha, Janet Kemei, Michelle Lalonde, Jemal Nur, Wale Ajiboye, Ilene Hyman, Sanni Yaya, Hugues Loemba, Robin Taylor, Bagnini Kohoun, Kyokusinga Kirunga, Onyenyechukwu Nnorom, Sane Dube, Wangari Tharao, Lovelyn Ubangha, Bishwajit Ghose
Rok vydání: 2021
Předmět:
Zdroj: Global Journal of Health Science. 14:75
ISSN: 1916-9744
1916-9736
DOI: 10.5539/gjhs.v14n1p75
Popis: BACKGROUND: The ongoing COVID-19 pandemic has emerged as an unprecedented challenge for public and private life, and healthcare systems worldwide. African, Caribbean, and Black communities (ACB) represent some of the most vulnerable populations in terms of their susceptibility to health hazards, difficulty receiving adequate health care and relatively lower chances of recovery. OBJECTIVES: The main aim of this study is to improve the health system’s response during and after the COVID-19 pandemic by developing evidence-based models to inform policy and collaborative best practices to mitigate its spread and ameliorate related health consequences in vulnerable communities. METHODS: This is a mixed-method, multisite study based in Ottawa and Toronto that will involve in-depth qualitative interviews and surveys using a structured questionnaire. Data will be analyzed using NVivo for qualitative interviews, Stata 16 and IBM SPSS version 26 for statistical analyses. DISCUSSION: The findings of this study gained from highly professional health practitioners will produce strong evidence on current gaps in knowledge and practice in the healthcare system’s capacity to meet the health needs of ACB population. The distinct insights and perspectives will be disseminated with policymakers and researchers at all levels which will facilitate strategic policy making with the goal of addressing the unique challenges for health
Databáze: OpenAIRE
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