Registered Nurses' Familiarity With Delegation Standards and Confidence Delegating to Unlicenced Care and Support Workers: A Cross-Sectional Study

Abstract

Aim: To survey registered nurses' familiarity with delegation standards and confidence to delegate to unlicenced workers within their practice. Design: Cross-sectional exploratory survey design. Methods: The survey focused on Australian registered nurses (n = 420). Initial descriptive analysis was undertaken. Additionally, inferential analysis was undertaken between two independent variables focused on familiarity of delegation policy, and confidence to delegate, and several demographic and workplace variables. Stepwise linear regression was undertaken to determine predictors of the two delegation variables. The cross-sectional study was undertaken according to the STROBE reporting checklist. Results: The majority of respondents were somewhat familiar, or not familiar at all with delegation standards. This pattern was followed for results relevant to confidence delegating to unlicenced workers. Nurses working in adult acute, intensive care and emergency department reported the lowest levels of familiarity with delegation. Additionally, intensive care nurses were significantly less likely to feel very confident delegating to unlicenced support workers. Stepwise regression revealed identifying as male, and working in the public sector were less likely to be confident delegating. Nurses working in the acute setting and public sector were less familiar with delegation standards. Conclusion: The findings of this study highlight the nuanced nature of delegation to unlicenced workers in Australian nursing settings, with nurses from certain contexts being far less likely to be familiar with or confident undertaking the practice. Implications for Clinical Practice: The findings of this study have significant implications to increase understanding of nurses diverse contexts of practice and how delegation standards might not be implemented in practice in a confident manner.