Analysis of variables affecting employees’ absenteeism in a special employment center

Abstract

Background

The literature has studied different personal variables and their possible relationship with absenteeism. These variables are age, gender, tenure in the firm, professional category, type of disability, and type of contract. This paper addresses the study of these variables from the perspective of people with disabilities and how they can affect this group.

Objective

The study of absenteeism is of great importance since it is considered one of the problems that negatively influence production and, therefore, the success of the organization. However, there are currently few contributions relating absenteeism to work within the group of people with disabilities. Consequently, this research aims to fill this research gap and examines the factors affecting absenteeism in a Special Employment Center (SEC), a company where around 90% of its employees have disabilities, to determine how personal characteristics can affect absenteeism (among the group with disabilities) and help establish some possible human resource policies for managing this situation.

Methods

The methodology used in the research is observational as no intervention or manipulation is performed by the researchers. The study is statistical and longitudinal, focusing on measuring the variables presented over a period of three years. Thus, this paper presents an empirical analysis of the real levels of absence among a group of employees in an SEC in the city of Cartagena (Murcia, Spain) from the data provided by a historical series between the years 2019 and 2021. The absenteeism rates have been calculated according to various personal variables to identify which of them are representative of absenteeism levels. The data collected were analyzed using SPSS version 23.0^® and Microsoft Excel 365^®. This study follows the STROBE guidelines.

Results

Significant differences were found among absenteeism rates for the variables “tenure in the firm” (pvalue = 0.0022) in the group of employees with more than 21 years’ seniority. For the “professional category” variable (pvalue = 0.016), the second and third officers’ groups showed differences from the other groups, and “type of disability” (pvalue = 0.0302) showed differences for the mental and physical groups. Other variables, such as age (55 to 67-year-old employees had the highest absenteeism rates), gender (absenteeism was more prevalent among men), and type of contract (absenteeism was higher among employees with permanent contracts), were also analyzed. In these cases, however, the absenteeism rates were not statistically significant (pvalue = 0.06443 for age; pvalue = 0.3911 for gender; and pvalue = 0.2935 for type of contract).

Conclusions

When applying human resource policies at the company level, variables with significant differences in absenteeism levels should be monitored. This would allow human resources practitioners to concentrate on these variables and groups with the highest rates of absenteeism and adequately adjust their policies. Some recommendations are to create an inclusive organizational culture where more vulnerable people are the priority. For example, additional support should be given to mentally and physically disabled workers through the use of buddy systems, and interviews could determine their difficulties and the adjustments the firm must provide. Work-life balance policies that can help reduce absenteeism are also mentioned in the paper.