The National and Global Impact of Systemic and Structural Violence on the Effective Prevention, Treatment, and Management of COVID-19 in African or Black Communities: Protocol for a Scoping Review
Notice bibliographique
Résumé
BACKGROUND: As COVID-19 ravages the globe and cases increase rapidly, countries are presented with challenging policy choices to contain and mitigate its spread. In Canada and globally, the COVID-19 pandemic has added a new stratum to the debate concerning the root causes of global and racial health inequities and disparities. Individuals who exist as targets of systemic inequities are not only more susceptible to contracting COVID-19, but also more likely to bear the greatest social, economic, and physical burdens. Therefore, data collection that focuses on the impact of COVID-19 on the lives and health of African/Black communities worldwide is needed to develop intersectional, culturally relative, antiracist/antioppression, and empowerment-centered interventions and social policies for supporting affected communities. OBJECTIVE: The primary objective of this review is to investigate the impact and management of COVID-19 among African/Black individuals and communities, and understand how anti-Black racism and intersectional violence impact the health of African/Black communities during the pandemic. Moreover, the study aims to explore research pertaining to the impact of COVID-19 on Black communities in the global context. We seek to determine how Black communities are impacted with regard to structural violence, systematic racism, and health outcomes, and the ways in which attempts have been made to mitigate or manage the consequences of the pandemic and other injurious agents. METHODS: A systematic search of quantitative and qualitative studies published on COVID-19 will be conducted in MEDLINE (Ovid), Embase (Ovid), Cumulative Index to Nursing and Allied Health Literature (EBSCO), Cochrane Library, PsychInfo (Ovid), CAB Abstracts (Ovid), Scopus (Elsevier), Web of Science (Clarivate), and Global Index Medicus. To be included in the review, studies should present data on COVID-19 in relation to African/Black individuals, populations, and communities in the global sphere. Studies must discuss racism, oppression, antioppression, or systemic and structural violence and be published in English, French, Spanish, or Portuguese. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, the findings will be synthesized quantitatively and qualitatively through thematic analysis. The risk of bias will not be assessed. RESULTS: Title, abstract, and full-text screening concluded in June 2022. Data collection is in progress and is expected to be completed by December 2022. Data analysis and drafting of the manuscript will be done thereafter. Findings from the scoping review are expected to be provided for peer review in 2023. CONCLUSIONS: This review will collect important data and evidence related to COVID-19 in African/Black communities. The findings could help identify existing gaps in COVID-19 management in African/Black communities and inform future research paradigms. Furthermore, the findings could be applied to decision-making for health policy and promotion, and could potentially influence services provided by health care facilities and community organizations around the globe. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40381.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,084 | 0,099 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,011 | 0,018 |
| Bibliométrie | 0,016 | 0,013 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,010 | 0,008 |
| Science ouverte | 0,006 | 0,008 |
| Intégrité de la recherche | 0,010 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,074 | 0,011 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».