Digital tools for identifying work tasks in various occupations: A scoping review

This scoping review aimed to map peer-reviewed studies applying digital tools for automatically or semi-automatically mapping work tasks, including their type, location, duration, or worker identification. Following Arksey and O'Malley's framework and PRISMA-ScR guidelines, systematic searches were conducted in PubMed, Web of Science, and Google Scholar (2014-2024). Forty-nine studies were included, most of which were of moderate quality, limited by small and unrepresentative samples and low user involvement. Studies covered diverse occupations, mainly construction (n = 20) and manufacturing (n = 16). The most common tools were sensor-based (n = 24), vision-based (n = 13), multimodal (hybrid) (n = 6), and localisation-based (n = 4). Audio- and interaction-based tools appeared in single studies. Many tools captured task duration, some also worker identity, and fewer captured task location. These findings highlight both the potential and the current limitations of digital tools for mapping work tasks, underscoring the need for methodological development and real-world application in occupational research and practice. The protocol was preregistered in the Open Science Framework (OSF): https://doi.org/10.17605/OSF.IO/U7PBT.