Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/10581
Title: Predicting variations to missed nursing care: a three-nation comparison
Authors: Blackman, Ian 
Papastavrou, Evridiki 
Palese, Alvisa 
Vryonides, Stavros 
Henderson, Julie 
Willis, Eileen 
Keywords: Australia;Cyprus;Italy;Missed nursing;Multi-variate analysis
Category: Health Sciences
Field: Medical and Health Sciences
Issue Date: Jan-2018
Publisher: John Wiley & Sons Ltd
Source: Journal of Nursing Management, 2018, Volume 26, Issue 1, Pages 33-41
metadata.dc.doi: https://doi.org/10.1111/jonm.12514
Abstract: Aims: To measure and model Australian, Cypriot and Italian nurses’ beliefs about what care is missed and how frequently it occurs within their settings. Background: This study expands on previous MISSCARE research but now applies and predicts missed care within three countries. Methods: Multivariate analysis was performed to estimate 1,896 nurses’ consensus scores about missed care activities based on Alfaro-Lefevre’s conceptual framework of care priorities. Results: Five latent variables have direct predictor effects on missed care frequencies. Another four variables including the nurses’ age, highest qualifications, absenteeism rate and workplace type, contributed to explaining the overall variance of missed care scores. The nurses’ gender had no influence on missed care. Conclusion: Cross country comparisons of missed nursing care allow for a more refined identification of strategies for remediation for both managers and clinicians. Implications for Nursing Management: Reliable consensus estimates about the types and frequencies of missed care can be scaled with variables identified to predict missed care across three different countries. Comparative international studies build on the foundations for understanding missed care in terms of nursing practices, policies and related social policies.
URI: http://ktisis.cut.ac.cy/handle/10488/10581
ISSN: 09660429
Rights: © 2017 John Wiley & Sons Ltd
Type: Article
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