Discrimination experienced by Asian Canadian and Asian American health care workers during the COVID-19 pandemic: a qualitative study
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
<h3>Background:</h3> Asian Canadians and Asian Americans face COVID-19–related discrimination. The objective of this qualitative study was to explore the experiences of Asian health care workers dealing with discrimination, with a focus on racial micro-agressions, in Canada and the United States during the COVID-19 pandemic. <h3>Methods:</h3> We adopted a qualitative descriptive approach. We used convenience and snowball sampling strategies to recruit participants. We conducted individual, in-depth semistructured interviews with Asian health care workers in Canada and the US via videoconferencing between May and September 2020. Eligible participants had to self-identify as Asian and be currently employed as a health care worker with at least 1 year of full-time employment. We used an inductive thematic approach to analyze the data. <h3>Results:</h3> Thirty participants were recruited. Fifteen (50%) were Canadians and 15 (50%) were Americans; there were 18 women (60%), 11 men (37%) and 1 nonbinary person. Most of the participants were aged 25–29 years (<i>n</i> = 16, 53%). More than half were nurses (<i>n</i> = 16, 53%); the other participants were attending physicians (<i>n</i> = 5), physiotherapists (<i>n</i> = 3), resident physicians (<i>n</i> = 2), a midwife, a paramedic, a pharmacist and a physician assistant. Two themes emerged from the data: a surge of racial microaggressions related to COVID-19 and a lack of institutional and public acknowledgement. Participants noted that they have experienced an increase in racial microaggressions during the COVID-19 pandemic. They have also experienced threats of violence and actual violence. The largely silent organizational response to the challenges being faced by people of Asian descent and the use of disparaging terms such as “China virus” in the early stages of the pandemic were a substantial source of frustration. <h3>Interpretation:</h3> Asian health care workers have experienced challenges in dealing with racial microaggressions related to COVID-19 in the US and Canada. More research should be done on the experiences of Asian Americans and Asian Canadians, both during and after the pandemic, and supportive measures should be put in place to protect Asian health care workers.
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle