Background The standard approach for assessing lifetime individual occupational exposure is the manual collection and coding of self-reported job-histories. However this process is time-consuming and unfeasible in large population-based studies such as the UK Biobank cohort. Our aim was to develop a new valid and efficient web-based tool to collect, and automatically code, individual lifetime job-histories in the UK Biobank cohort to investigate work-related COPD.
Methods UK Biobank is a population-based cohort of 502,682 subjects, aged 40–69 years, recruited in 2006–2010. We developed an online job-questionnaire, termed OSCAR (Occupations Self Coding Automatic Recording tool), based on the hierarchical structure of the UK Standard Occupational Classification (SOC) 2000 to allow participants to self-collect and automatically code their lifetime job-histories via a decision tree model. Each participant was asked to identify each job through lists of job categories ending in a job title linked to a hidden 4-digit SOC-code. Also for each job a job title in free text was collected to allow OSCAR validation. Cohen’s kappa coefficient (k) was used to estimate inter-rater agreement between SOC codes assigned by OSCAR and by an expert manual coder (gold standard).
Results OSCAR was submitted in June-August 2015 to the 324,653 Biobank participants with an available email. Lifetime 4-digit SOC-coded job-histories for 108,784 responders were obtained (participation rate 34%). A random sample of 400 job titles in free text was used to perform OSCAR validation. The agreement between the 4-digit SOC codes assigned by OSCAR and the manual coder was moderately good (k = 0.46; 0.42–0.49). The agreement improved when considering job categories (0.70 at a 1-digit SOC-code level).
Conclusions Our web-based job questionnaire OSCAR is a new efficient and valid tool for collecting and automatically coding lifetime job histories in large population-based studies and is adaptable for use in other health research projects.
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