JMIR Publications

ABSTRACT

Background:

Artificial intelligence (AI) is an umbrella term for various algorithms and rapidly emerging technologies that bear huge potential for workplace health promotion and prevention (WHPP). WHPP interventions aim at improving the health and well-being of people at work through a combination of behavioral and organizational measures or by minimizing the burden of workplace-related diseases and associated risk factors. While AI has been in the focus of research in other health related fields such as Public Health or biomedicine, the transition of AI into WHPP research has not been systematically investigated.

Objective:

To describe and critically reflect studies applying AI in specific WHPP fields, the following research questions (RQ) were answered: (1) what are the study characteristics of studies on AI algorithms and technologies in the context of WHPP, (2) what specific WHPP fields (prevention, behavioral and organizational approaches) were addressed by the AI algorithms and technologies, and (3) what kind of interventions were conducted and what outcomes were assessed?

Methods:

A systematic scoping literature review (PRISMA-ScR) was conducted in the three academic databases PubMed, IEEE and ACM in July 2023 searching for articles published between January, 2000 and July, 2023. Studies needed to be 1) peer-reviewed, 2) written in English, and 3) focused on any AI-based algorithm or technology that (4) were conducted in the context of WHPP or (5) an associated field. Information on study design, AI algorithms and technologies, WHPP fields and the PICO framework were extracted in a blinded way with Rayyan and summarized.

Results:

A total of nine studies were included. Risk prevention and modelling were the most identified WHPP fields (n=5), followed by behavioral health promotion (n=4) and organizational health promotion (n=1). Most AI algorithms were machine learning-based, three studies used combined deep learning-algorithms. AI-algorithms and technologies were mostly implemented in smartphone applications (eg, in form of a Chatbot) or used the smartphone as a data source (eg, GPS). Behavioral approaches ranged from 8 to 12 weeks and were compared to control groups. Three studies evaluated the robustness and accuracy of an AI model or framework.

Conclusions:

Although AI has caught an increasing attention in health-related research, the review reveals that AI in WHPP is marginally investigated. Our results indicate that AI might be promising for WHPP, but current studies are rather at a prototype stage. Beyond, the results of our review showed, that there is a strong need to transparently report aspects of data protection in further studies. Clinical Trial: Registered on 5th July, 2023 at Open Science Framework [1]