Providing newborn care in eat sleep console: A qualitative exploration of nurses’ experiences
Notice bibliographique
Résumé
,Perinatal substance use and neonatal withdrawal are increasing across Canada, creating significant challenges for families and the healthcare system. Traditional approaches to care, which rely heavily on pharmacological interventions, often result in prolo nged and costly admissions to neonatal intensive care units (NICUs). In response to these concerns, a team in the United States developed the Eat, Sleep, Console (ESC) model, which shifts the focus toward parental involvement and non-pharmacological care strategies rather than highly medicalized NICU care. In British Columbia, the ESC model has been adapted to emphasize trauma informed and culturally safe principles, placing greater responsibility on perinatal nurses who provide dyad care. Exploring nurses’ experiences of delivering newborn care within this model is essential to understanding the relational, clinical, and workload demands they face. Gaining insight into these perspectives is critical for supporting the sustainability of ESC in practice. An integrative literature review of 18 articles revealed that nurses’ experiences of caring for newborns with neonatal abstinence syndrome is complex and multifaceted. However, most of the existing evidence centers on NICU nurses and emphasizes traditional, pharmacological approaches. The perspectives of perinatal nurses, particularly those providing neonatal withdrawal care in settings outside the NICU, remain underexplored. To address this gap, this study set out to explore how perinatal nurses in Northern British Columbia experience providing newborn care in the context of ESC. Using Interpretive Description as the guiding methodology, semi-structured interviews were conducted with six perinatal nurses in one northern community. Data were analyzed thematically through an iterative coding process that began with structural coding aligned to the research questions, followed by pattern coding to identify broader themes across the dataset. The findings suggest that nurses experienced ESC care as complex and labour-intensive, requiring them to move well beyond the provision of direct newborn care. Their work encompassed fostering relationships with parents, providing extensive teaching to sup port parental independence, and managing the dynamics of team-based practice change. The overarching theme, The Work Really Isn’t About the Baby, reflected this emphasis, and was further articulated through three main themes: The Work Perinatal Nurses DO for ESC, TeamWORK in ESC, and the Work to embrace the change. Overall, the study highlights a persistent tension between the holistic intentions of ESC and the biomedical, task-oriented structures that continue to shape healthcare delivery. Nurses’ experiences illustrate the need for stronger organizational and structural supports to sustain trauma informed, culturally safe, and relational care, especially in the face of fluctuating patient volumes and entrenched systemic pressures. The clinical implications of these findings point to the importance of policies and staffing models that recognize the acuity of both newborns and their parents. Providing adequate capacity for nurses to deliver relational, family-centered care is essential. Strengthening interdisciplinary collaboration and supplementing limited social supports with dedicated roles can help reduce nursing burden and improve care for families affected by substance use disorders. Finally, organizational commitment to trauma informed and culturally safe practice is crucial for optimizing ESC implementation and fostering trust with families.
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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 | 0,008 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,010 | 0,009 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,003 |
| 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 ».