Canadian critical care nurses experiences on the front lines of the COVID-19 pandemic: a qualitative descriptive study
Notice bibliographique
Résumé
BACKGROUND: Recent pandemics have provided important lessons to inform planning for public health emergencies. Despite these lessons, gaps in implementation during the COVID-19 pandemic are evident. Additionally, research to inform interventions to support the needs of front-line nurses during a prolonged pandemic are lacking. We aimed to gain an understanding of critical care nurses' perspectives of the ongoing pandemic, including their opinions of their organization and governments response to the pandemic, to inform interventions to improve the response to the current and future pandemics. METHODS: This sub-study is part of a cross-sectional online survey distributed to Canadian critical care nurses at two time points during the pandemic (March-May 2020; April-May 2021). We employed a qualitative descriptive design comprised of three open-ended questions to provide an opportunity for participants to share perspectives not specifically addressed in the main survey. Responses were analyzed using conventional content analysis. RESULTS: One hundred nine of the 168 (64.9%) participants in the second survey responded to the open-ended questions. While perspectives about effectiveness of both their organization's and the government's responses to the pandemic were mixed, most noted that inconsistent and unclear communication made it difficult to trust the information provided. Several participants who had worked during previous pandemics noted that their organization's COVID-19 response failed to incorporate lessons from these past experiences. Many respondents reported high levels of burnout and moral distress that negatively affected both their professional and personal lives. Despite these experiences, several respondents noted that support from co-workers had helped them to cope with the stress and challenges. CONCLUSION: One year into the pandemic, critical care nurses' lived experiences continue to reflect previously identified challenges and opportunities for improvement in pandemic preparedness and response. These findings suggest that lessons from the current and prior pandemics have been inadequately considered in the COVID-19 response. Incorporation of these perspectives into interventions to improve the health system response, and support the needs of critical care nurses is essential to fostering a resilient health workforce. Research to understand the experience of other front-line workers and to learn from more and less successful interventions, and leaders, is needed.
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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 | 0,011 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,024 | 0,009 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».