Abstract
Intensive care topics were taught by clinical nurse experts in structured lectures covering several critical care topics including pulmonary catheters, external pacing, massive transfusion, prone therapy, cardiopulmonary arrest, Minnesota/Blakemore tubes, continuous renal replacement therapy and rapid sequence intubation at a large academic university medical center in the southeastern United States.
Among a small sample of newly hired intensive care nurses (P) who attended ICU lectures (I) how much did they improve (C) their scores for confidence in caring for patients with specific conditions (O)?
Through the analysis of the empirical data collected in a simple matched-response pretest and posttest survey it was recognized that conventional inferential statistics (e.g., t-tests) used to analyze the data collected in a non-randomized one group pretest posttest design in a healthcare setting generally provide biased and misleading results. For this reason, Knapp (2012, p.467) argued “Why is the one-group pretest posttest design still used? In the context of research in nursing, Spurlock (2018, p. 69) recommended: “the single-group pre- and post-test design in nursing education research: it’s time to move on”. (The sample size used in the present study was only N = 10 and therefore inferential statistics were underpowered.
Dendrograms were used depicting the results of the hierarchical cluster analysis to classify the ten nurses by their confidence in caring for patients with specific conditions before and after the intervention (i.e., ICU lectures).
The conclusion is that a p-value, or statistical significance, does not measure the size of an effect or the importance of a result.” (Wasserstein et al., 2016, p.129). The nursing science community is implored to abandon the language of statistical significance in favor of meaningful statistics.
Notes
Reference list included in attached slide deck.
Sigma Membership
Non-member
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Other
Keywords:
Acute Care, Teaching and Learning Strategies, Academic-clinical Partnership, Nursing Education, Advances in Education, New Hire Nurses, New Graduate Nurses, Competence, Intensive Care Unit Nurses
Recommended Citation
Klein, Bryan A.; Keathley, Laken; and Rogers, Sandra, "Improving Confidence in Newly Hired Medicine ICU Registered Nurses" (2025). Biennial Convention (CONV). 200.
https://www.sigmarepository.org/convention/2025/presentations_2025/200
Conference Name
48th Biennial Convention
Conference Host
Sigma Theta Tau International
Conference Location
Indianapolis, Indiana, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. 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
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2025-12-08
Improving Confidence in Newly Hired Medicine ICU Registered Nurses
Indianapolis, Indiana, USA
Intensive care topics were taught by clinical nurse experts in structured lectures covering several critical care topics including pulmonary catheters, external pacing, massive transfusion, prone therapy, cardiopulmonary arrest, Minnesota/Blakemore tubes, continuous renal replacement therapy and rapid sequence intubation at a large academic university medical center in the southeastern United States.
Among a small sample of newly hired intensive care nurses (P) who attended ICU lectures (I) how much did they improve (C) their scores for confidence in caring for patients with specific conditions (O)?
Through the analysis of the empirical data collected in a simple matched-response pretest and posttest survey it was recognized that conventional inferential statistics (e.g., t-tests) used to analyze the data collected in a non-randomized one group pretest posttest design in a healthcare setting generally provide biased and misleading results. For this reason, Knapp (2012, p.467) argued “Why is the one-group pretest posttest design still used? In the context of research in nursing, Spurlock (2018, p. 69) recommended: “the single-group pre- and post-test design in nursing education research: it’s time to move on”. (The sample size used in the present study was only N = 10 and therefore inferential statistics were underpowered.
Dendrograms were used depicting the results of the hierarchical cluster analysis to classify the ten nurses by their confidence in caring for patients with specific conditions before and after the intervention (i.e., ICU lectures).
The conclusion is that a p-value, or statistical significance, does not measure the size of an effect or the importance of a result.” (Wasserstein et al., 2016, p.129). The nursing science community is implored to abandon the language of statistical significance in favor of meaningful statistics.
Description
Educational experiences for newly hired nurses should be measured by more than statistical significance. The nursing science community should be more concerned of meaningful statistics which can be used for healthcare decision making. Clinical relevance should be the primary product of our research inquiry. We need to go beyond the p-value when looking at the value of educational experiences such as critical care courses for the newly hired registered nurse.