•  
  •  
 

Abstract

Purpose: The purpose of this quantitative correlational study was to determine if, or to what extent, the composite and sub-composite categories of Psychological Capital (PsyCap) predict academic burnout in American postgraduate health science students at a university in the Southeastern United States. Methods: The variables of the study were measured by the Psychological Capital Questionnaire (PCQ-24) and the Maslach Burnout Inventory-Student Survey (MBI-SS). A convenience sampling method was used to collect data from the target population, which included a final sample of 90 health science postgraduate students. Results: A simple linear regression analysis revealed that PsyCap was a significant and negative predictor of academic burnout (F(1,88) = 12.00, p < .001, R2 = 0.12; B = -0.28, t(88) = -3.46, p < .001). Additionally, multiple linear regression analysis revealed that only one sub-category of PsyCap, labeled as Optimism, was a significant and negative predictor of academic burnout (F(4,85) = 5.17, p < .001, R2= 0.20; B = -0.90, t(85) = -3.17, p = .002). Conclusion: The findings may be used by higher education instructors, advisors, and administrators in the United States to adopt policies, practices, programs, student advising, and student mentorship that foster PsyCap and Optimism development in students, which may mitigate the risks and consequences of academic burnout.

Author Bio(s)

  1. Benjamin M Radack, PT, DPT, EdD is an Assistant Professor in the School of Physical Therapy at the University of Lynchburg.

  2. Theodus Luckett III, EdD is the Director of Fine Arts at Mount Pleasant Independent School District and is a Senior Dissertation Chair in the College of Doctoral Studies at Grand Canyon University.

  3. Wade W. Fish, PhD is a Special Populations Coordinator for the Forney, Texas Independent School District.

  4. Gary P. Austin, PT, PhD, is a Professor and Chair of the School of Physical Therapy at Belmont University.

Share

Submission Location

 
COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.