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<p>This study aimed to describe the competence profiles, practices, job satisfaction, and interprofessional collaboration among nurses working in Italian anticoagulation clinics (ACs) affiliated with the Italian federation of centres for the surveillance of anticoagulant therapy (FCSA). Data were collected via a web survey from December 2023 to May 2024. The information was condensed into two stochastic components using the <i>t</i>-distributed stochastic neighbour embedding (t-SNE) algorithm as part of the hierarchical clustering procedure, revealing two distinct clusters labelled “substandard profile” (<i>n</i> = 21 nurses) and “proficient profile” (<i>n</i> = 38 nurses). Results indicated significant variability in nursing practices, with differences in educational activities, self-reported competence, and levels of interprofessional collaboration between the two clusters. The findings underscore the importance of tailored interventions to enhance nursing practices, nursing education, and interprofessional collaboration within ACs. Future corroboration of the emerging results is warranted with longitudinal studies.</p>

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Exploring Italian nursing staff in anticoagulation clinics: a cluster-based description of current practice, nurse self-efficacy, job satisfaction, and interprofessional collaboration

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月11日

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  • Arianna Magon,
  • Rosario Caruso,
  • Cristina Arrigoni,
  • Marcello Torre,
  • Antonio M. G. Staffa,
  • Marco Paolo Donadini,
  • Walter Ageno,
  • Alessandro Squizzato,
  • Paolo Bucciarelli,
  • Antonio Ciampa,
  • Daniela Poli

摘要

This study aimed to describe the competence profiles, practices, job satisfaction, and interprofessional collaboration among nurses working in Italian anticoagulation clinics (ACs) affiliated with the Italian federation of centres for the surveillance of anticoagulant therapy (FCSA). Data were collected via a web survey from December 2023 to May 2024. The information was condensed into two stochastic components using the t-distributed stochastic neighbour embedding (t-SNE) algorithm as part of the hierarchical clustering procedure, revealing two distinct clusters labelled “substandard profile” (n = 21 nurses) and “proficient profile” (n = 38 nurses). Results indicated significant variability in nursing practices, with differences in educational activities, self-reported competence, and levels of interprofessional collaboration between the two clusters. The findings underscore the importance of tailored interventions to enhance nursing practices, nursing education, and interprofessional collaboration within ACs. Future corroboration of the emerging results is warranted with longitudinal studies.