Predicting teacher retention using stress and support variables

Daniel A. Sass (The University of Texas at San Antonio, San Antonio, Texas, USA)
Andrea K. Seal (The University of Texas at San Antonio, San Antonio, Texas, USA)
Nancy K. Martin (The University of Texas at San Antonio, San Antonio, Texas, USA)

Journal of Educational Administration

ISSN: 0957-8234

Publication date: 22 March 2011



Teacher attrition is a significant international concern facing administrators. Although a considerable amount of literature exists related to the causes of job dissatisfaction and teachers leaving the profession, relatively few theoretical models test the complex interrelationships between these variables. The goal of this paper is to partially fill this gap.


Using a sample of 479 certified teachers who taught either at elementary (55.3 percent), middle (33.0 percent), or high (10.6 percent) school levels, three competing theoretical models with variables related to teacher stress or support were tested using structural equation modeling to predict job dissatisfaction and eventual intention to quit.


The most parsimonious model revealed that student stressors completely mediated the relationship between teacher efficacy related to student engagement and job dissatisfaction, with social support superiors and student stressors being best predictors of job dissatisfaction. Although important within the school system, teacher workload stressors and social support from colleagues did not contribute significantly to the models.


Theoretical models are needed to assist school administrators and researchers in developing programs to improve teacher retention and to predict those teachers who will struggle within the profession. Moreover, developing and testing comprehensive models associated with variables related to teacher and student success is critical for a well functioning school system.



Sass, D., Seal, A. and Martin, N. (2011), "Predicting teacher retention using stress and support variables", Journal of Educational Administration, Vol. 49 No. 2, pp. 200-215.

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