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Using ordinal logistic regression to analyze job satisfaction among three generations of physicians

Author: Jaciel Keltgen
Publisher: London : SAGE Publications Ltd, 2019.
Series: SAGE Research Methods., Cases.
Edition/Format:   eBook : Document : English
Summary:
This dissertation employed neo-institutional theory to hypothesize job satisfaction factors among three generations of American physicians before passage of the Affordable Care Act (ACA), and was intended to lay the foundation for job satisfiers most important for Millennial physicians. Forecasts suggest there will be a shortage of physicians to serve an aging populace; therefore, health care employers may need to  Read more...
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Jaciel Keltgen
ISBN: 9781526474407 1526474409
OCLC Number: 1084521619
Description: 1 online resource.
Series Title: SAGE Research Methods., Cases.
Responsibility: Jaciel Keltgen.

Abstract:

This dissertation employed neo-institutional theory to hypothesize job satisfaction factors among three generations of American physicians before passage of the Affordable Care Act (ACA), and was intended to lay the foundation for job satisfiers most important for Millennial physicians. Forecasts suggest there will be a shortage of physicians to serve an aging populace; therefore, health care employers may need to change compensation packages to include more leisure time to retain doctors. I chose to conduct ordinal logistic regression analysis of data gathered by the Center for Studying Health System Change. Data were used to build a predictive statistical model in concert with independent variables associated with generational and job satisfaction literature. Independent variables included generational membership, gender, type of practice, years in practice, specialty, income, hours worked per week, and malpractice concerns. Using this method required me to switch from SPSS to Stata, learn to use the new statistical software, recode variables, learn to run specialized commands, and analyze statistically significant correlations between factors by generational membership (Traditionalists, Baby Boomers, and Generation Xers) and gender.

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