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Development and Validation of a Mass Casualty Conceptual Model
Author(s) -
Culley Joan M.,
Effken Judith A.
Publication year - 2010
Publication title -
journal of nursing scholarship
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.009
H-Index - 80
eISSN - 1547-5069
pISSN - 1527-6546
DOI - 10.1111/j.1547-5069.2009.01320.x
Subject(s) - delphi method , context (archaeology) , likert scale , conceptual model , construct (python library) , scale (ratio) , computer science , delphi , sample (material) , management science , data science , operations research , psychology , statistics , mathematics , engineering , artificial intelligence , paleontology , chemistry , chromatography , quantum mechanics , database , biology , physics , programming language , operating system
Purpose: To develop and validate a conceptual model that provides a framework for the development and evaluation of information systems for mass casualty events. Design: The model was designed based on extant literature and existing theoretical models. A purposeful sample of 18 experts validated the model. Open‐ended questions, as well as a 7‐point Likert scale, were used to measure expert consensus on the importance of each construct and its relationship in the model and the usefulness of the model to future research. Methods: Computer‐mediated applications were used to facilitate a modified Delphi technique through which a panel of experts provided validation for the conceptual model. Rounds of questions continued until consensus was reached, as measured by an interquartile range (no more than 1 scale point for each item); stability (change in the distribution of responses less than 15% between rounds); and percent agreement (70% or greater) for indicator questions. Findings: Two rounds of the Delphi process were needed to satisfy the criteria for consensus or stability related to the constructs, relationships, and indicators in the model. The panel reached consensus or sufficient stability to retain all 10 constructs, 9 relationships, and 39 of 44 indicators. Experts viewed the model as useful (mean of 5.3 on a 7‐point scale). Conclusions: Validation of the model provides the first step in understanding the context in which mass casualty events take place and identifying variables that impact outcomes of care. Clinical Relevance: This study provides a foundation for understanding the complexity of mass casualty care, the roles that nurses play in mass casualty events, and factors that must be considered in designing and evaluating information‐communication systems to support effective triage under these conditions.