Health System Leadership for Psychological Health and Organizational Resilience During the COVID-19 Pandemic: Protocol for a Multimethod Study
Notice bibliographique
Résumé
BACKGROUND: Since the World Health Organization declared COVID-19 a global pandemic, health systems and health system leaders have faced unprecedented challenges through the various stages of the crisis. Canada and other health systems were largely ill-prepared to handle this crisis. The longevity of the pandemic has profoundly affected health care systems and compounded the rates of negative psychological outcomes in health systems' leaders and staff, rates of emotional exhaustion, and burnout. OBJECTIVE: The purpose of this study is to investigate the experiences of health system leaders and nurses during COVID-19 and to develop recommendations to inform pre-, during-, and postcrisis leadership strategies and practices for health system leaders, which address leaders' and nurses' psychological health and well-being, as well as organizational resilience. METHODS: A 3-year multimethod approach will be adopted and include a qualitative exploratory inquiry informed by Geerts' 4-stage framework of imperatives for health system leaders to guide data collection and analysis. We will then conduct semistructured individual interviews with health system leaders in 3 provinces in Canada and hold focus group interviews (FGIs) with nurses from the same organizations. Data from the interviews and FGIs will be integrated to determine how health system leaders promoted their own health and how their leadership shaped nurses' psychological health and contributed to building organizational resilience. We will engage knowledge users using a nominal group technique in a 1-day forum to discuss how findings can be applied in professional contexts. We will conduct a thematic analysis of the aggregated data to identify and analyze themes to provide an interpretive explanation of health system leaders' experiences and organizational resilience during the COVID-19 pandemic, and how the leaders promoted nurses' psychological health and well-being. The protocol has been reviewed and approved by the University of Manitoba institutional review board (IRB), the University of Alberta IRB, and McMaster University Ontario IRB. RESULTS: As of September 6, 2024, this study has made significant progress. Data collection has been completed for individual interviews with health leaders in Alberta and Manitoba, and has commenced in Ontario. FGIs will be completed by the fall of 2025, data integration in early 2026, nominal group technique in the spring of 2026, and the final report will be written in the summer of 2026. CONCLUSIONS: The findings will support practices that health system leaders can implement to foster their own and nurses' psychological health and well-being and build organizational resilience. The benefits of this study aim to include evidence for effective health system leadership and support for nurses, crisis preparedness, and lessons from the pandemic to address leadership practices to operationalize the imperatives within the 4 stages of the crisis model. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/66402.
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 | 0,076 | 0,074 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,004 |
| Méta-épidémiologie (sens large) | 0,006 | 0,005 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,009 | 0,004 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,008 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,096 | 0,019 |
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 ».