OBJECTIVES: In today's working world, the use of digital services is widespread and has an impact on job satisfaction, which is a part of quality of life. Typically, job satisfaction and psychological problems such as stress or burnout are negatively correlated. The large amounts of data generated by digital services and the possibility to analyze them with machine intelligence offer the opportunity to develop objective methods to measure job satisfaction. This project deals with the objective measurement of job satisfaction in the context of digital services and the prevention of mental health problems.

METHODS: The factors influencing job satisfaction will be collected through a systematic literature review. Based on the current state of knowledge, a model with objectively measurable indicators of job satisfaction will be developed. This model will be empirically tested with data from individuals using digital services. The data will be collected automatically and will provide information on usage patterns as well as stress. A complementary survey will be used to capture the subjective assessment of job satisfaction and compare it to the objective measures. An AI model based on machine learning will be developed that can objectively calculate job satisfaction based on the available data.

RESULTS: The systematic literature review identified several factors that significantly influence job satisfaction. A job satisfaction model was created using measurable indicators such as hours worked, workload intensity, digital engagement, and service usage patterns. Preliminary results from the AI model show trends and patterns that correlate the use of digital services with higher or lower levels of job satisfaction.

CONCLUSIONS: This project provides an innovative approach to objectively measure job satisfaction in the digital world. By understanding the relationship between digital service use, job satisfaction, and mental health, the project may provide preliminary insights into strategies for preventing stress and burnout in the workplace.