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How to Assess the External Validity and Model Validity of Therapeutic Trials: A Conceptual Approach to Systematic Review Methodology

Background. Evidence rankings do not consider equally internal (IV), external (EV), and model validity (MV) for clinical studies including complementary and alternative medicine/integrative medicine (CAM/IM) research. This paper describe this model and offers an EV assessment tool (EVAT©) for weighi...

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Detalles Bibliográficos
Autores principales: Khorsan, Raheleh, Crawford, Cindy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3963220/
https://www.ncbi.nlm.nih.gov/pubmed/24734111
http://dx.doi.org/10.1155/2014/694804
Descripción
Sumario:Background. Evidence rankings do not consider equally internal (IV), external (EV), and model validity (MV) for clinical studies including complementary and alternative medicine/integrative medicine (CAM/IM) research. This paper describe this model and offers an EV assessment tool (EVAT©) for weighing studies according to EV and MV in addition to IV. Methods. An abbreviated systematic review methodology was employed to search, assemble, and evaluate the literature that has been published on EV/MV criteria. Standard databases were searched for keywords relating to EV, MV, and bias-scoring from inception to Jan 2013. Tools identified and concepts described were pooled to assemble a robust tool for evaluating these quality criteria. Results. This study assembled a streamlined, objective tool to incorporate for the evaluation of quality of EV/MV research that is more sensitive to CAM/IM research. Conclusion. Improved reporting on EV can help produce and provide information that will help guide policy makers, public health researchers, and other scientists in their selection, development, and improvement in their research-tested intervention. Overall, clinical studies with high EV have the potential to provide the most useful information about “real-world” consequences of health interventions. It is hoped that this novel tool which considers IV, EV, and MV on equal footing will better guide clinical decision making.