Survey of Unreported Psychiatric Morbidity Induced by Job Dissatisfaction among Teachers: Inferential Point of View
Ajibola T. Soyinka *
Department of Statistics, Federal University of Agriculture, Alabata, Abeokuta Ogun state, Nigeria.
Shola Oyetola
Department of Psychiatry, University of Calgary, 2500 University Dr NW, Alberta T2N1N4, Calgary, Canada.
Akinlolu A. Olosunde
Department of Mathematics, Obafemi Awolowo University, Ile-ife, Osun state, Nigeria.
Oluwaseun A. Wale-Orojo
Department of Statistics, Federal University of Agriculture, Alabata, Abeokuta Ogun state, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Elegant statistical methods for categorical data analysis are rapidly evolving and being adopted, particularly for biomedical and social sciences data analysis. This study presents a case study for the application of the discrete Johnson systems of distribution approach for the analysis of secondary school teachers’ job satisfaction (JS). This new approach accommodates relative frequency behavioural patterns in the analysis of categorical data using the entropy measure of discrete Johnson systems of distribution (DJSD). The approach offers a better alternative to the existing chi-square and likelihood ratio tests because it captures more shared information compared to known measures of association. A focus on the JS of about 393 teachers, showed that above 60% of the teacher’s eventually developed job dissatisfaction induced psychiatric disorders before the end of their career. Further examples were used to illustrate the applicability of the approach and enhance its reproducibility.
Keywords: Psychiatric morbidity, job (dis)satisfaction, teachers, discrete Johnson system distribution, inferential properties, entropy