Literature DB >> 27973677

Occupational self-coding and automatic recording (OSCAR): a novel web-based tool to collect and code lifetime job histories in large population-based studies.

Sara De Matteis1, Deborah Jarvis, Heather Young, Alan Young, Naomi Allen, James Potts, Andrew Darnton, Lesley Rushton, Paul Cullinan.   

Abstract

Objectives The standard approach to the assessment of occupational exposures is through the manual collection and coding of job histories. This method is time-consuming and costly and makes it potentially unfeasible to perform high quality analyses on occupational exposures in large population-based studies. Our aim was to develop a novel, efficient web-based tool to collect and code lifetime job histories in the UK Biobank, a population-based cohort of over 500 000 participants. Methods We developed OSCAR (occupations self-coding automatic recording) based on the hierarchical structure of the UK Standard Occupational Classification (SOC) 2000, which allows individuals to collect and automatically code their lifetime job histories via a simple decision-tree model. Participants were asked to find each of their jobs by selecting appropriate job categories until they identified their job title, which was linked to a hidden 4-digit SOC code. For each occupation a job title in free text was also collected to estimate Cohen's kappa (κ) inter-rater agreement between SOC codes assigned by OSCAR and an expert manual coder. Results OSCAR was administered to 324 653 UK Biobank participants with an existing email address between June and September 2015. Complete 4-digit SOC-coded lifetime job histories were collected for 108 784 participants (response rate: 34%). Agreement between the 4-digit SOC codes assigned by OSCAR and the manual coder for a random sample of 400 job titles was moderately good [κ=0.45, 95% confidence interval (95% CI) 0.42-0.49], and improved when broader job categories were considered (κ=0.64, 95% CI 0.61-0.69 at a 1-digit SOC-code level). Conclusions OSCAR is a novel, efficient, and reasonably reliable web-based tool for collecting and automatically coding lifetime job histories in large population-based studies. Further application in other research projects for external validation purposes is warranted.

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Year:  2016        PMID: 27973677     DOI: 10.5271/sjweh.3613

Source DB:  PubMed          Journal:  Scand J Work Environ Health        ISSN: 0355-3140            Impact factor:   5.024


  5 in total

1.  Development of a Coding and Crosswalk Tool for Occupations and Industries.

Authors:  Thomas Rémen; Lesley Richardson; Corinne Pilorget; Gilles Palmer; Jack Siemiatycki; Jérôme Lavoué
Journal:  Ann Work Expo Health       Date:  2018-08-13       Impact factor: 2.179

2.  Physical work exposure matrix for use in the UK Biobank.

Authors:  E L Yanik; M J Stevens; E Clare Harris; K E Walker-Bone; A M Dale; Y Ma; G A Colditz; B A Evanoff
Journal:  Occup Med (Lond)       Date:  2022-02-22       Impact factor: 1.611

3.  Burnout syndrome in Europe: towards a harmonized approach in occupational health practice and research.

Authors:  Irina Guseva Canu; Olivia Mesot; Christina Györkös; Zakia Mediouni; Ingrid Sivesind Mehlum; Merete Drevvatne Bugge
Journal:  Ind Health       Date:  2019-02-27       Impact factor: 2.179

4.  Important Difference between Occupational Hazard Exposure among Shift Workers and Other Workers; Comparing Workplace before and after 1980.

Authors:  Maud Miguet; Gull Rukh; Olga E Titova; Helgi B Schiöth
Journal:  Int J Environ Res Public Health       Date:  2020-10-15       Impact factor: 3.390

5.  Is occupational physical activity associated with mortality in UK Biobank?

Authors:  Matthew Pearce; Tessa Strain; Katrien Wijndaele; Stephen J Sharp; Alexander Mok; Søren Brage
Journal:  Int J Behav Nutr Phys Act       Date:  2021-07-27       Impact factor: 6.457

  5 in total

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