INVESTIGATION OF RISK FACTORS PERCEPTION LEVELS IN PUBLIC AND PRIVATE SECTOR INSTITUTIONS FOR WORKERS IN THE OFFICE ENVIRONMENT
DOI:
https://doi.org/10.38064/eurssh.209Keywords:
Office Environment, Risk Factors, Occupational Health and Safety, Public and Private Sector, Statistical DataAbstract
Workplaces are divided into three as very dangerous, dangerous and less dangerous according to the principle of the work done. When occupational accidents and diseases are mentioned, construction sites and mines are considered. However, although the probability of occupational accidents and diseases is low, most working areas throughout the country are offices. In the offices, there are obligations that the employer must fulfill according to the law numbered 6331. Employees in offices that accommodate employees from all levels of the public and private sector are likely to be exposed to risk factors. Office workers are most exposed to physical, psychosocial and ergonomic risk factors. The employer is likely to prevent work accidents and occupational diseases by providing a healthy and safe working environment for its employees. In this study, a questionnaire consisting of 28 questions was applied to examine the perception levels of physical, psychosocial and ergonomic risk factors for 246 office workers in public and private sector institutions in Samsun. The answers to the questionnaire questions were analyzed with the program "IBM SPSS Statistics 22.0" and the value of "Cronbach Alpha (α)" was found to be 0.667. The fact that α value is in the range of 0.6 <α <0.8 indicates that the study is reliable. As a result of the study, the majority of the participants are women, the 26-33 age group, undergraduate graduates and work in public institutions. We found that the level of perception of psychosocial risk factors depends on monthly income, the level of perception of ergonomic risk factors changes depending on the sector and weekly working period, and the level of perception of physical risk factors does not change depending on demographic data.
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