Resilience throughout COVID-19: Unmasking the realities of COVID-19 and vaccination facilitators, barriers, and attitudes among Black Canadians
Notice bibliographique
Résumé
Black communities have suffered disproportionately higher numbers of COVID-19 cases and deaths in Canada. Recognizing the significance of supporting targeted strategies with vulnerable populations extends beyond the COVID-19 pandemic, as it addresses longstanding health disparities and promotes equitable access to healthcare. The present study investigated 1) experiences with COVID-19, 2) COVID-19's impact, and 3) factors that have influenced COVID-19 vaccine acceptance and uptake among stakeholders and partners from the Federation of Black Canadians' (FBC). We conducted semi-structured interviews with 130 individuals and four focus groups with FBC, including stakeholders and partners, between November 2021 and June 2022. The semi-structured interviews and focus group discussions were conducted virtually over Zoom and lasted about 45 minutes each. Conversations from interviews and focus groups were transcribed and coded professionally using team-based methods. Themes were developed using an inductive-deductive approach and defined through consensus. The deductive approach was based on Consolidated Framework for Implementation Research (CFIR) domains and constructs. First, regarding experiences with COVID-19, 36 codes were identified and mapped onto 13 themes. Prominent themes included 39 participants who experienced highly severe COVID-19 infections, 25 who experienced stigma, and 18 who reported long recovery times. Second, COVID-19 elicited lifestyle changes, with 23 themes emerging from 62 codes. As many as 97 participants expressed feelings of isolation, while 63 reported restricted mobility. Finally, participants discussed determinants that influenced their vaccination decisions, in which 46 barriers and four facilitators were identified and mapped onto nine overarching themes. Themes around the CFIR domains Individuals, Inner Setting, and Outer Setting were most prominent concerning vaccine adoption. As for barriers associated with the constructs limited available resources and low motivation, 55 (41%) and 46 (34%) of participants, respectively, mentioned them most frequently. Other frequently mentioned barriers to COVID-19 vaccines fell under the construct policies & laws, e.g., vaccine mandates as a condition of employment. Overall, these findings provide a comprehensive and contextually rich understanding of pandemic experiences and impact, along with determinants that have influenced participants' vaccination decisions. Furthermore, the data revealed diverse experiences within Black communities, including severe infections, stigma, and vaccine-related challenges, highlighting the importance of targeted interventions, support, and consideration of social determinants of health in addressing these effects.
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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 | 0,005 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,021 | 0,010 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».