This study was conducted to determine if specialty areas are emerging in the magnetic resonance imaging (MRI) profession due to advancements made in the medical sciences, imaging technology, and clinical applications used in MRI that would require new developments in education/training programs and national registry examinations. In this exploratory study, statistical analysis incorporated the use of factor analysis and chi square. Factor analysis was used to group tasks performed by MRI technologists into factors to better identify emerging specialty areas within the MRI profession. Chi square was used to analyze the association between the tasks performed in (a) the employment setting, and (b) hospital size. Factor analysis identified four meaningful factors. The four named factors were: (a) Routine Imaging non-Central Nervous System Imaging; (b) Advanced Imaging; (c) Routine Imaging with Central Nervous System Imaging; and (d) Musculoskeletal and Spine Imaging. From the four named factors, three emerging specialty areas were identified: (a) central nervous system imaging; (b) vascular/cardiovascular imaging; and (c) musculoskeletal imaging. Chi square analysis identified 47 of the 78 tasks as being significant when finding an association between the employment setting and the frequency of tasks performed. Cramer's V was used to measure the strength of their association. The more complicated the procedure the more likely this procedure is performed in either a university or private hospital. Further, chi square analysis identified 42 of the 78 tasks as being significant when finding the association between the hospital size and the frequency of tasks performed. Gamma was used to measure the strength of their association. This means the larger the hospital, the more frequent the tasks were performed.
Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:dissertations-1070 |
Date | 01 December 2009 |
Creators | Grey, Michael L. |
Publisher | OpenSIUC |
Source Sets | Southern Illinois University Carbondale |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Dissertations |
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