Compassionate leadership in healthcare: creating a culture where every voice matters.

  • Published In: Nursing Standard, 2026, v. 41, n. 3. P. 59 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Heyes, Stephanie Louise 3 of 3

Abstract

Why you should read this article: • To enhance your knowledge of the principles of compassionate leadership • To learn some techniques that you could use to embed compassionate leadership into your daily practice • To contribute towards revalidation as part of your 35 hours of CPD (UK readers) • To contribute towards your professional development and local registration renewal requirements (non-UK readers). Nurses and other healthcare professionals are required to provide care in an increasingly pressured and complex environment, placing greater demands on the workforce. Compassionate leadership offers a values-driven alternative to traditional hierarchical leadership. Rooted in empathy, active listening and meaningful action, compassionate leadership can help to establish psychological safety, whereby team members feel safe to speak up, raise concerns, share ideas and learn from mistakes without fear of blame or punishment. This article explores the critical relevance of this leadership approach for modern nursing and explains how it aligns with the evolving needs of the healthcare workforce. It also offers practical, evidence-based approaches for nurses to embed compassionate leadership into their daily practice, promoting inclusive, supportive and empowered teams where every voice is truly heard and valued. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Nursing Standard. 2026/03, Vol. 41, Issue 3, p59
  • Document Type:Article
  • Subject Area:Sociology
  • Publication Date:2026
  • ISSN:0029-6570
  • DOI:10.7748/ns.2026.e12617
  • Accession Number:192012421
  • Copyright Statement:Copyright of Nursing Standard is the property of Royal College of Nursing of the United Kingdom (The) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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