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Enregistrement W4410478716 · doi:10.1155/jonm/6634676

The Implementation of Infection Prevention and Control Procedures in Primary Care During the COVID‐19 Pandemic: A Qualitative Study of Nursing Roles

2025· article· en· W4410478716 sur OpenAlexafffundabout
Samina Idrees, Maria Mathews, Lindsay Hedden, Julia Lukewich, Emily Gard Marshall, Kelly Kean, Rhiannon Lyons, Jamie Wickett, Leslie Meredith, Dana Ryan, Sarah Spencer, Émilie Dufour, Paul Gill

Notice bibliographique

RevueJournal of Nursing Management · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueCOVID-19 and healthcare impacts
Établissements canadiensNewfoundland and Labrador Centre for Applied Health ResearchDalhousie UniversityGovernment of Newfoundland and LabradorMemorial University of NewfoundlandSimon Fraser UniversityWestern University
Organismes subventionnairesCanadian Institutes of Health ResearchCanada Research Chairs
Mots-clésThematic analysisPandemicNursingWorkloadQualitative researchMedicinePrimary careHealth carePsychologyCoronavirus disease 2019 (COVID-19)Family medicinePolitical scienceSociology

Résumé

récupéré en direct d'OpenAlex

Introduction: During the COVID‐19 pandemic, primary care practices felt poorly supported by existing infection prevention and control (IPAC) guidelines, which focused primarily on acute care facilities. This issue was further complicated by insufficient provision of personal protective equipment in primary care settings, which limited clinic capacity and the ability of primary care to provide in‐person services. Nurses play an integral role in the implementation of IPAC procedures and the provision of ongoing primary care during a health crisis; however there is limited literature related to nurses’ roles in the enactment of IPAC procedures in primary care settings. This paper aims to describe primary care nurses’ experiences and roles in implementing IPAC during the COVID‐19 pandemic. Design: Qualitative analysis of interviews as part of a larger mixed methods case study. Methods: We conducted semistructured qualitative interviews with primary care nurses across four Canadian regions in the provinces of British Columbia, Ontario, Nova Scotia, and Newfoundland and Labrador. During the interviews, we asked participants to describe the roles they enacted during the various stages of the pandemic, any facilitators and challenges they encountered, and the potential roles that nurses could have played. We employed a thematic analysis approach, and, for the purposes of this paper, we analyzed themes relevant to the implementation of IPAC. Results: We interviewed 76 nurses across the four regions and identified two overarching themes: (1) nurse‐led transformation of clinic operations and (2) impact on workload. Primary care nurses developed and implemented IPAC policies, educated staff, and made critical decisions about patient care, often out of necessity and ahead of regional guidelines. In addition, nurses adapted workflows, managed supplies, and balanced in‐person and virtual care to protect both patients and staff from COVID‐19 exposure. Conclusion: Despite the additional responsibilities and challenges that nurses faced in response to evolving guidelines, their IPAC efforts were pivotal in maintaining primary care clinic operations during the pandemic. The findings from this study underscore primary care nurses’ capacity to adapt and apply evidence‐based practices and demonstrate the need for better pandemic planning to support primary care. IPAC guidance documents, suitable for primary care settings and informed by experiences from the COVID‐19 pandemic, should be included in future pandemic plans. Implications for Nursing Management: Our findings highlight the need for stronger institutional support and preparedness for primary care nurses during a pandemic. Nursing management should ensure that IPAC responsibilities are explicitly recognized within primary care nursing roles and supported through ongoing training, resource allocation, and standardized protocols. Proactively integrating IPAC into primary care practice and strengthening these supports will enhance future health crisis preparedness while mitigating nurse burnout and promoting sustainable workforce capacity.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,349
Score d'incertitude au seuil0,289

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,063
Tête enseignante GPT0,504
Écart entre enseignants0,441 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2025
Routes d'admission3
Résumé présentoui

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