The Association between Job Stress and Productivity among the Non-Academic Staff of Universities

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Extended Abstract
Background
Given that human resources (HR) and employees are critical assets of organizations, their productive performance is considered the main element of an organization's success. Job stress is a crucial predictive variable for HR performance; hence, studying and identifying the elements that affect HR performance is important. The effectiveness of an organization's human resources is an important aspect of HR productivity, and job stress is one of its inhibitors. This study aimed to determine the relationship between job stress and HR productivity among the staff of Ahvaz Jundishapur University of Medical Sciences (AJUMS) in Ahvaz, Iran.
Methods
This cross-sectional study initially included 108 employees of AJUMS, selected randomly using Cochran's formula. However, the initial sample size was raised by 15%, to 124, to account for potential attrition. The data collection tool included three parts. First, the demographic characteristics form to collect demographic variables such as gender, age, education level, and marital status, as well as job-related information such as job experience and position. Second, the occupational stress questionnaire (HSE) encompassed 35 items based on a 5-point Likert scale, with a score range between 35 and 175. This questionnaire consisted of dimensions such as employee position, communication, management support, colleague support, control, demand, and change. Third, Hersey and Blanchard's questionnaire titled "Achieve’s Productivity Questionnaire" contained 32 questions in seven components, which were workability, role clarity or perception, organizational support, willingness to motivate, feedback or evaluation, credibility, and environmental compatibility. In Achieve’s Productivity Questionnaire, the answers are scored based on the Likert scale (very little (1), little (2), to some extent (3), a lot (4), and very much (5)). The minimum score of the questionnaire is 32, and the maximum score is 160. Finally, the data was analyzed using SPSS V22. Moreover, mean and standard deviation, as well as Chi-square, Pearson correlation coefficient, and regression tests, were used for descriptive and inferential statistical analysis. This study was conducted after obtaining permission from the Research Council and approval from the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (code of ethics: IR.AJUMS.REC.1400.668).
Results
The participation rate was 97.5% among selected participants based on sample size. The mean age of the participants was 32.72 (±6.67) years. A total of 61 (50.4%) and 60 (49.6%) participants were male and female, respectively. Regarding the level of education, most of the participants, 74 (61.2 %), had a bachelor's degree. The mean scores of job stress and job performance were 119.75 (±17.49) and 103.3 (±21.47), respectively, and both variables were estimated at average levels. Demand (24.43±5.79) and control (21.08±4.14) variables had the highest mean among job stress variables. Also, among job performance variables, organizational support (25.37±7.60) and willingness to motivate (17.17±4.66) had the highest mean. There was a significant negative association between job stress and job performance (r= -0.59, P> 0.001). In addition, employee position, management support, and change were three stress subscales identified as the main predictors of employee productivity based on linear regression. Some demographic variables (age, gender, and education level) showed significant differences in occupational stress scores based on subgroup analysis.
Conclusion
There is a significant negative correlation between occupational stress and AJUMS' staff productivity. The results of this study can be generalized to university administrative personnel. Considering the negative relationship between job stress and staff productivity, university managers should have sufficient knowledge and awareness of stressful factors and consider these factors in their policies and decisions. Three occupational stress components, including management support, change, and employee position, were identified as main predictors of productivity. Therefore, in order to improve productivity, managers need to consider more independence in decision-making and support for personnel, as well as reduce the changes’ rate.