Aims And Objectives: To examine the influence of workplace incivility on the quality of nursing care.
Background: Recent evidence describes workplace incivility as a serious concern in the healthcare setting worldwide. Exposure to workplace incivility can alter a nurse's behaviour, thought process and perspective towards the nursing profession. However, there is insufficient evidence to determine whether workplace incivility might be associated with the quality of nursing care in Saudi Arabia.
Design: A quantitative and cross-sectional study.
Method: A survey was carried out amongst 378 nurses in two government hospitals in Saudi Arabia from February 2018-May 2018 using the Nurse Incivility and quality of nursing care scales. Multivariate multiple regression was performed to investigate the influence of the uncivil experiences of nurses from different sources on the different aspects of quality of nursing care. The study adhered to STROBE guideline (see Appendix S1).
Results: The overall mean of the quality of nursing care scale was 3.14 (SD = 0.66) from a scale of 1-5, with patient satisfaction receiving the highest mean dimension (mean = 3.27, SD = 0.72) and health promotion the lowest mean dimension (mean = 3.08, SD = 0.74). Experience in the present hospital and the hospital were associated with the overall quality of nursing care. General and nurse incivility exerted a multivariate effect on overall quality of nursing care and its different dimensions.
Conclusion: General incivility and nurse incivility were found to negatively impact quality of nursing care and its different dimensions.
Relevance To Clinical Practice: Stronger policies geared towards eliminating workplace incivility should be implemented as uncivil acts can lead to poor quality of nursing care. Nurse administrators and nurses should be pro-active in recognising, preventing, approaching, reporting and intervening with uncivil acts in the hospital to protect these workers from these types of behaviours and avoid their negative impacts on patient care.
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http://dx.doi.org/10.1111/jocn.15051 | DOI Listing |
Clin Nurs Res
January 2025
College of Nursing, University of Tennessee Health Science Center, Memphis, TN, USA.
Atherosclerotic cardiovascular disease (ASCVD) risk calculators estimate the 10-year incident risk of myocardial infarction (MI), coronary artery disease (CAD) death, or stroke; however, they lack comprehensiveness and accuracy. Carotid intima-media thickness (CIMT) is a surrogate marker that may improve risk estimation acumen. The objective of this study was to derive ASCVD risk scores from historical data and determine whether these risk scores are associated with the history of subclinical CAD and CIMT.
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January 2025
School of Nursing and Midwifery, Queen's University Belfast, Belfast, Northern Ireland, UK.
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January 2025
Department of Nursing and Health Promotion, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
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View Article and Find Full Text PDFCan J Anaesth
January 2025
Department of Medicine, Sinai Health and University of Toronto, Toronto, ON, Canada.
Purpose: The use of patient/family-centred written summaries to supplement verbal information may be useful to improve knowledge and reduce anxiety related to patient transfer from the intensive care unit (ICU) to a hospital ward. We aimed to identify essential elements to include in an ICU-specific patient-oriented discharge summary tool (PODS-ICU).
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Sci Rep
January 2025
The Second Affiliated Hospital of ZunYi Medical University, Zunyi, Guizhou, China.
It is crucial to determine the potential subgroups of sleep disturbances in patients undergoing elective surgery based on the importance of symptom clusters and individual characteristics in order to develop targeted symptom management plans. This study explored the potential categories of postoperative sleep disturbances in patients undergoing elective surgery through latent profile analysis, and explored the influencing factors of each category. A total of 400 eligible elective surgery patients were included in the analysis, and three potential subgroups were identified: mild sleep disturbance group (c1 = 140,35.
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