Introduction: Research on shift work and working time arrangements is often hindered by inconsistencies
in how working hours and core features are reported and by the substantial amount
of time that is necessary to understand such time arrangements and to compute additional
variables. To address these issues, we propose the development of a server-based platform
for collecting, standardizing, descriptions of working hours in research and automatically
calculating many features of these working hours. This platform will serve as a centralized
repository where researchers can describe, categorize, and compare studies on shift
work and working time arrangements systematically.
Methods: DESCRIPTION ELEMENT A: WORKING TIME DESCRIPTION To ensure cross-study consistency
and comparability, we propose three potential approaches for describing working time
characteristics: 1. Actual Working Hours in a Standardized Format: Work periods are
recorded using a universally recognized time format (e.g., 24-hour notation), ensuring
precision and consistency. 2. Standardized Statistical Descriptors: Shift schedules
are characterized using statistical measures such as mean start and end times, variability
in shift duration, and frequency of night shifts. 3. Shift Similarity Descriptors:
A concise, standardized notation to represent schedules that allows for translation
into actual hours. DESCRIPTION ELEMENT B: RESEARCH OUTCOMES & WORK CHARACTERISTICS
To facilitate cross-study comparisons, we also propose standardized methods for describing
research results, with labels that can be defined by users: • Availability and Access:
Clear metadata indicating where articles and datasets are available. • Measurement
Scales: Standardized recording of results using established scales e.g., scores on
the Karolinska Sleepiness Scale (KSS), reaction times, biomarkers. • Work Characteristics:
Free-text labels and structured sub- labels for capturing contextual factors (e.g.,
sector, workload intensity, exposure to rotating shifts).
Results: To support data standardization and enhance usability, we suggest the development
of an open-source software package that: • Computes many relevant shift-related features
based on the selected working time description. It should be easy to add additional
indicators or variables. • Provides filtering and querying capabilities, enabling
users to select datasets based on criteria such as shift length, time-of-day effects,
etc. • Allows authors to add a link to their paper, that gives immediate access to
a large number of indicators/features. By this, other researchers identify studies
more easily and can conduct different cross-study comparisons with greater accuracy.
Conclusion: This initiative aims to improve consistency, comparability, and accessibility of
research on working hours. By providing a centralized standardized shift descriptions,
outcome measures, and analytical tools, we can enhance collaboration across research
groups and facilitate the integration of findings into policy and occupational health
recommendations. This platform will foster greater collaboration among researchers,
support meta-analyses and reviews, policy development, and ultimately contribute to
better-informed occupational health and labor policies.
