Predicting Job Satisfaction Based on the Activity of Three Brain-Behavioral Systems: An Interdisciplinary Approach

Job satisfaction is one of the main concerns for organizations. It's widely related to other important parts of life including mental and physical health, job performance, and organizational productivity. According to the literature, personality variables are very important for predicting job satisfaction due to their relative stability. The present study has considered the neuropsychological and personality variable of reinforcement sensitivity, which is defined based on the activity of three behavioral brain systems, including Behavioral Activation System (BAS), Behavioral Inhibition System (BIS), and Fight, Flight, Freeze System (FFFS) as predictors of job satisfaction; Because it allows people to predict job satisfaction even before they have been employed by organization and organizations can select people with more likely future job satisfaction. It is also true that the level of activity of brain-behavioral systems is initially determined genetically; But in the future, it is also influenced by environmental factors and learning. Therefore, by considering the effect of the activity of each system on job satisfaction, it is possible to increase the possibility of more job satisfaction in people by making appropriate changes in environmental conditions and learning. In this way, organizations can determine the level of activity of systems in each of their current employees, to strengthen the appropriate brain-behavioral system in them to increase their job satisfaction and reduce the activity of system which activity is inversely related to job satisfaction. In this way, the individual, the organization, and, as a result, the whole of society will be able to benefit from more job satisfaction and the problems of less job satisfaction will be reduced.  

The research design was descriptive correlational. The statistical population was all Iran's employees in early 2018 with at least one year of work experience in their current position and at least a diploma degree. The minimum sample size was determined using the Green formula and the final sample of 321 people was determined by the convenient sampling method. Tools were MSQ- short form, and the Jackson Reinforcement Sensitivity Scale (r-RST) which were distributed via a Telegram robot designed for this special purpose. Data were analyzed using Multiple Regression Analysis in SPSS software version 26.

The results of regression analysis showed that Behavioral Activation System (BAS) has a positive significant relationship with job satisfaction (β=0.17, p < 0.002), and also the Behavioral Inhibition System (BIS) has a positive significant relationship with job satisfaction (β=0.15, p < 0.007). The best predictor was the Freeze subsystem with β= -0.26 and then the Fight subsystem with β=-0.20, which have a negative significant relationship with job satisfaction.

Considering the predictive role of three brain-behavioral systems for job satisfaction, these can be useful for predicting and increasing job satisfaction.