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Psychosocial Risks Assessment in Cryopreservation Laboratories.

Ana Fernandes¹, Margarida Figueiredo^1,2, Jorge Ribeiro³

¹Departamento de Química, Escola de Ciências e Tecnologia, Universidade de Évora, Évora, Portugal.

Safety and Health at Work

|December 17, 2020

Summary

Organizations are increasingly focused on managing psychosocial risks, such as interpersonal issues and stress, in the workplace. This study developed an artificial neural network model to predict and enhance psychosocial risk management in a cryopreservation lab.

Keywords:

Artificial neural networks Cryopreservation laboratories Health and safety management Psychosocial risks Risk assessment

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Area of Science:

Occupational Health and Safety
Organizational Psychology
Data Science

Background:

Psychosocial risks are gaining prominence in organizational safety management, alongside traditional chemical, physical, and biological hazards.
Updates to ISO 9001:2015 and the transition to ISO 45001 emphasize the importance of managing the work environment, including psychosocial factors.
Organizations are increasingly committed to demonstrating strong occupational health and safety performance.

Purpose of the Study:

To characterize psychosocial risks within a cryopreservation laboratory setting.
To develop a predictive model for effective psychosocial risk management.
To enhance organizational awareness and mitigation strategies for workplace stressors.

Main Methods:

A questionnaire-based inquiry was administered to a sample of 200 employees.
Data analysis involved identifying key factors contributing to psychosocial risks.
Artificial neural networks were employed to build a predictive model.

Main Results:

Employees recognize interpersonal relationships and emotional well-being as primary psychosocial risk factors.
Lack of resources, working hours, equipment, stress, and job insecurity strongly correlate with psychosocial risks.
The developed artificial neural network model demonstrated high predictive accuracy for psychosocial risks.

Conclusions:

An intelligent system was developed to identify organizational weaknesses related to psychosocial risks.
The system aids in enhancing the management of psychosocial risks.
This research contributes to improving occupational health and safety by addressing psychosocial factors.