Occupational Health Practice: Future-Oriented, Interdisciplinary, and Evidence-Based with AI (BAKI)

Department of Occupational, Social and Preventive Medicine

Virtual work can promote health, but it also comes with specific risks and challenges for occupational health practice. Current occupational safety and health solutions only partially meet the needs of virtually employed workers; visibility and access for occupational physicians are limited, and evidence-based digital tools are lacking. For these reasons, the Federal Institute for Occupational Safety and Health (BAuA) recommends supporting both occupational physicians and virtually employed workers through digital solutions.

Project Description

BAKI addresses these research gaps by examining how occupational health practice in virtual teams can be supported digitally and further developed on an evidence-based foundation in line with a holistic preventive approach. Using a participatory, human-centered, and iterative process, BAKI develops a digital learning assistance system consisting of two modules.

Module 1 collects multimodal physical, psychological, social, organizational, and technical data from virtually working employees that are relevant to occupational health practice. These data are analyzed and used to identify, classify, and predict predictors of health-related outcomes and to generate individual resource and risk profiles. This enables the identification of new leverage points for occupational health practice and the derivation of predictive approaches for prevention.

Module 2 explores, develops, and evaluates telemedicine possibilities—such as social virtual reality (VR) and chatbots—to strengthen the visibility and accessibility of occupational physicians and workplace health management (BGM) measures in the context of virtual teams through digital social spaces.

Methodology

The development of the assistance system is based on a multi-method approach that integrates methods from occupational medicine, psychology, data science, and human–computer interaction. This enables needs-based technology development, participatory examination of how occupational physicians and virtual workers interact, and the practical development, evaluation, and integration of the two system modules.

The system is intended to support occupational health practice for virtual workers by:

• identifying specific strains, stressors, and resources of virtual employees,

• deriving resource and risk profiles to provide individualized preventive and health-promoting support,

• assigning workplace health management (BGM) measures to individual profiles and identifying BGM needs,

• increasing the visibility of occupational health expertise—particularly regarding BGM measures—and improving access to occupational physicians, and

• evaluating the potentials and challenges of using artificial intelligence (AI) in occupational medicine.

Through the establishment of this junior research group, interdisciplinary competence profiles with diverse development opportunities in forward-looking research fields are created.

The project is funded through the FoGa – Research for Health in the Working World program.

Are You Interested?

The BAKI project is currently seeking cooperation partners for data collection. We are looking for companies willing to support the project by participating in data collection. In return, we offer integration into the project as well as future access to the tools developed within it.

If you are interested, please refer to the linked documents, where all requirements and advantages of participating in the project are described in detail.

Call for Abstracts

Following a successful premiere in 2024, the KI-Werkstatt (AI Workshop) will take place for the second time on March 17, 2026. Together with TU Dortmund, the Lamarr Institute, and the Research Center for Trustworthy Data Science and Security, we once again invite you to an interdisciplinary exchange on artificial intelligence in the working world — this time with the theme: Research Meets Practice.

• Research overview