Abstract
Sepsis is a devastating, life-threatening disease and a major problem for many newborns; it develops rapidly and requires expertise to identify the early, subtle signs to prevent death or disability. Evidence from nursing practice and philosophic inquiry indicates that nurses use diverse ways of knowing in their assessments. The purpose of this research was to address research questions concerning two areas: 1) Neonatal Intensive Care Unit (NICU) nurses' patterns of knowing in the assessment of infants with sepsis as related to dimensions of nursing practice; and 2) Test the psychometric properties of the Newborn Scale of Sepsis (SOS) as a diagnostic or assessment tool. The theoretical framework incorporated the epistemological theories of nurses Carper and Benner and philosopher of science Nagel.
Sigma Membership
Non-member
Lead Author Affiliation
Creighton University, Omaha, Nebraska, USA
Type
Dissertation
Format Type
Text-based Document
Study Design/Type
Descriptive/Correlational
Research Approach
Quantitative Research
Keywords:
Neonatal Intensive Care Nurses, Infants, Sepsis
Advisor
Pamela Reed
Second Advisor
Elaine G. Jones
Third Advisor
Linda Chapman
Fourth Advisor
Donna Christensen
Degree
PhD
Degree Grantor
The University of Arizona
Degree Year
2005
Recommended Citation
Rubarth, Lorraine B., "Nursing patterns of knowing in assessment of newborn sepsis" (2022). Dissertations. 267.
https://www.sigmarepository.org/dissertations/267
Rights Holder
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All permission requests should be directed accordingly and not to the Sigma Repository.
All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
None: Degree-based Submission
Acquisition
Proxy-submission
Date of Issue
2022-11-17
Full Text of Presentation
wf_yes
Description
This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 3162824; ProQuest document ID: 305026186. The author still retains copyright.