Nursing students' decision-making regarding postpartum hemorrhage: An exploration using the recognition-primed decision model.
Clinical decision-making
Clinical judgment
Knowledge
Naturalistic decision-making
Nurses
Nursing students
Postpartum hemorrhage
Recognition-Primed Decision Model
Journal
Nurse education in practice
ISSN: 1873-5223
Titre abrégé: Nurse Educ Pract
Pays: Scotland
ID NLM: 101090848
Informations de publication
Date de publication:
Oct 2022
Oct 2022
Historique:
received:
26
05
2022
revised:
25
08
2022
accepted:
31
08
2022
pubmed:
18
9
2022
medline:
19
10
2022
entrez:
17
9
2022
Statut:
ppublish
Résumé
To explore the knowledge content and structure of nursing students' decision-making in a high-stake clinical situation of postpartum hemorrhage using the Recognition-Primed Decision Model. According to research on clinical judgment, a nurse's expectations for a patient situation are central to the clinical decision-making process. However, little research has addressed the expectation concept and its relationship with the nurse's knowledge. Grounded in the naturalistic decision-making paradigm, the Recognition-Primed Decision Model provides a potential framework to describe the content and structure of nurses' knowledge and expectations as they unfold in high-stake clinical situations, such as postpartum hemorrhage. As it is typically used in studies of expert decision-making, it is crucial to test the adequacy of the Model with a student population and refine the research methods for using this framework. Descriptive design where qualitative data were analyzed using qualitative and quantitative methods. A convenience sample of 53 students enrolled in a maternal and child health course in the Fall of 2021 was formed. As part of an online exercise to prepare for a simulation, they read a vignette presenting the story of a woman experiencing postpartum hemorrhage and recorded their answers to questions designed to probe their decision-making. Recordings were transcribed and subjected to content analysis based on the four components of recognition according to the Recognition-Primed Decision Model (i.e., cues, expectations, goals and actions). All participants recognized the postpartum hemorrhage. Their knowledge was organized into clusters representing the potential causes (i.e., tone, trauma, tissue and thrombin) and consequences (i.e., hemodynamic instability) of postpartum hemorrhage, as well as other potential issues (e.g., pain and comfort, baby and partner, infection). Although students could identify relevant cues and actions, they had difficulties articulating their longer-term goals and expectations for the mother and care outcomes. This study showed the potential of the Recognition-Primed Decision Model to organize the content and structure of the knowledge that supported nursing students' decision-making in a high-stake situation. The findings suggest that their knowledge disproportionately focuses on the cause-and-effect relations between cues and actions. They invite further consideration of longer-term goals and expectations in nursing education to prepare students to anticipate events and assess patient responses appropriately.
Sections du résumé
AIM
OBJECTIVE
To explore the knowledge content and structure of nursing students' decision-making in a high-stake clinical situation of postpartum hemorrhage using the Recognition-Primed Decision Model.
BACKGROUND
BACKGROUND
According to research on clinical judgment, a nurse's expectations for a patient situation are central to the clinical decision-making process. However, little research has addressed the expectation concept and its relationship with the nurse's knowledge. Grounded in the naturalistic decision-making paradigm, the Recognition-Primed Decision Model provides a potential framework to describe the content and structure of nurses' knowledge and expectations as they unfold in high-stake clinical situations, such as postpartum hemorrhage. As it is typically used in studies of expert decision-making, it is crucial to test the adequacy of the Model with a student population and refine the research methods for using this framework.
DESIGN
METHODS
Descriptive design where qualitative data were analyzed using qualitative and quantitative methods.
METHODS
METHODS
A convenience sample of 53 students enrolled in a maternal and child health course in the Fall of 2021 was formed. As part of an online exercise to prepare for a simulation, they read a vignette presenting the story of a woman experiencing postpartum hemorrhage and recorded their answers to questions designed to probe their decision-making. Recordings were transcribed and subjected to content analysis based on the four components of recognition according to the Recognition-Primed Decision Model (i.e., cues, expectations, goals and actions).
FINDINGS
RESULTS
All participants recognized the postpartum hemorrhage. Their knowledge was organized into clusters representing the potential causes (i.e., tone, trauma, tissue and thrombin) and consequences (i.e., hemodynamic instability) of postpartum hemorrhage, as well as other potential issues (e.g., pain and comfort, baby and partner, infection). Although students could identify relevant cues and actions, they had difficulties articulating their longer-term goals and expectations for the mother and care outcomes.
CONCLUSIONS
CONCLUSIONS
This study showed the potential of the Recognition-Primed Decision Model to organize the content and structure of the knowledge that supported nursing students' decision-making in a high-stake situation. The findings suggest that their knowledge disproportionately focuses on the cause-and-effect relations between cues and actions. They invite further consideration of longer-term goals and expectations in nursing education to prepare students to anticipate events and assess patient responses appropriately.
Identifiants
pubmed: 36115258
pii: S1471-5953(22)00162-7
doi: 10.1016/j.nepr.2022.103448
pii:
doi:
Substances chimiques
Thrombin
EC 3.4.21.5
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
103448Informations de copyright
Copyright © 2022 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interest None.