Prediction of Radiography Certification Examination Scores Using Astin’s Input-Environment-Output Model

Abstract

Numerous health profession fields, including radiology, have attempted to identify predictors of success on their respective credentialing exams. This preregistered study seeks to determine if available academic performance measures may predict radiography national certification examination scores and help educators identify students for remediation and support. The study will use the Astin Input-Environment-Output Model, which ascertains that student outcomes are a result of what they bring into an academic program and the environment experienced during the program. The non-experimental retrospective study will look at the 2018 to 2021 Arkansas State University radiography cohorts. Multiple regression will be used to determine if reading comprehension, final course grade in college algebra, GPA in prerequisite sciences courses, and final grade in Image Acquisition and Evaluation II can predict success on the radiography certification examination. Findings from this study will help guide program admission criteria and identify students for remediation and support before taking the certification examination.

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