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OPERAS decision support system versus manual job coding: a quantitative analysis on coding time and inter-coder

Mathijs A Langezaal1,2, Egon L van den Broek2, Grégoire Rey3

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Summary
This summary is machine-generated.

Decision support systems (DSS) like OPERAS significantly improve job coding efficiency and reliability compared to manual methods. This automated approach saves time and enhances accuracy for occupational health research.

Keywords:
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Area of Science:

  • Occupational Health Research
  • Data Science
  • Sociology

Background:

  • Manual coding of job descriptions is resource-intensive, requiring significant time, cost, and specialized expertise.
  • Decision support systems (DSS) offer automated coding, potentially enhancing efficiency and consistency, but their effectiveness with expert coders needed validation.
  • The OPERAS DSS was developed to address these challenges in occupational coding.

Purpose of the Study:

  • To compare the efficiency and reliability of manual job description coding against coding assisted by the new DSS, OPERAS.
  • To evaluate the performance of OPERAS with expert coders using established French classification systems (PCS2003, NAF2008).
  • To assess the usability of the OPERAS system.

Main Methods:

  • Five expert coders performed job description coding both manually and using OPERAS.
  • Coding time and inter-coder reliability (using Cohen's kappa) for occupation (PCS) and activity sector (NAF) codes were measured.
  • System Usability Scale (SUS) was used to evaluate the perceived usability of OPERAS.

Main Results:

  • OPERAS significantly reduced coding time, with a median of 38 seconds per description compared to 60.8 seconds for manual coding.
  • Inter-coder reliability was higher with OPERAS (PCS: 0.61-0.70; NAF: 0.38-0.61) versus manual coding (PCS: 0.56-0.61; NAF: 0.34-0.61).
  • The average usability score for OPERAS was 75.5, indicating good user acceptance.

Conclusions:

  • The OPERAS DSS demonstrably improves both coding time and inter-coder reliability compared to traditional manual coding methods.
  • OPERAS is a valuable tool for facilitating large-scale, harmonized job coding in occupational health research.
  • Future research could explore OPERAS with international classification systems like ISCO-88 and ISCO-68.