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Demographic and spatial trends in diabetes-related virtual nursing examinations

Author

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  • Schultze, Steven R.
  • Mujica, Frances C.
  • Kleinheksel, A.J.

Abstract

Diabetes currently affects nearly 30 million Americans, but the distribution of cases is not uniform across all demographics or every state. In the course of their education, nurses learn how to become important conduits for information on diabetes management during their eventual interactions with patients. Exploring the status and trends of diabetes-related knowledge in nursing students is one method to explore the idea that one's community affects how one sees disease. However, they are not yet experts, which places them in a period of transition. This study used data mined from the Shadow Health Digital Clinical Experience™ virtual patient exams conducted by nursing students between the years of 2012 and 2015 to find any potential demographic or spatial trends within simulation performance results from nursing students who examined a virtual patient with self-managed diabetes. Findings of the analysis indicated that age and experience affected the way in which an examination was conducted, where older and more experienced nursing students asked 8% fewer examination questions, yet showed 32% more empathy and offered 76% more educational statements than their younger counterparts. Spatial trends were less pronounced, although deeper analysis revealed that students in states closer to the national mean for population rate with diabetes perform better, show more empathy, and offer more educational statements during examinations compared to states well above or well below the national mean. This suggests that targeted information may be preferable to "one-size-fits-all" public health awareness and education programs for diabetes programs used uniformly across the country.

Suggested Citation

  • Schultze, Steven R. & Mujica, Frances C. & Kleinheksel, A.J., 2019. "Demographic and spatial trends in diabetes-related virtual nursing examinations," Social Science & Medicine, Elsevier, vol. 222(C), pages 225-230.
    • Handle: RePEc:eee:socmed:v:222:y:2019:i:c:p:225-230
    DOI: 10.1016/j.socscimed.2019.01.002
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    References listed on IDEAS

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    1. Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
    2. Jasmin Schabert & Jessica Browne & Kylie Mosely & Jane Speight, 2013. "Social Stigma in Diabetes," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 6(1), pages 1-10, March.
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