Development and validation of a French job-exposure matrix for healthcare workers: JEM Soignances.

Abstract

Objectives: This study aimed to develop and evaluate a job-exposure matrix (JEM) specific to healthcare workers, JEM Soignances, based on self-reported data.

Methods: The JEM was constructed using data from healthcare workers within the CONSTANCES cohort (N=12 489). Job titles and sectors of activity (eg, hospital activities) defined occupational groups. We assessed 24 exposures covering organizational, psychosocial, physical, chemical and biological factors. Several methods (group-based frequency, CART, random forest, extreme gradient boosting machine) were applied using a 70% training sample. Performance was evaluated on the remaining 30% using area under the ROC curve (AUC) and Cohen's Kappa (κ). Two alternative JEM were proposed using only job titles or adding healthcare establishment size and type (public/private) to define occupational groups.

Results: All methods offered similar discriminatory power (AUC). We selected the group-based frequency method as it was the most understandable and easiest to implement. Of the 24 included exposures, 15 demonstrated satisfactory performance, with nine showing good discriminatory power and fair-to-moderate agreement, such as physical effort at work (AUC=0.861, κ=0.556), ionizing radiation exposure (AUC=0.865, κ=0.457), carrying heavy loads (AUC=0.840, κ=0.402), shift work (AUC=0.807, κ=0.383), and formaldehyde exposure (AUC=0.847, κ=0.289). The remaining nine exposures mainly showed poor-to-moderate discriminatory power and poor agreement. Compared to JEM Soignances, the job title-only JEM performed poorly, while the one incorporating healthcare establishment size and type showed similar results.

Conclusions: JEM Soignances provides good internal performance and validity. Future research will assess its external validity by comparing it with existing JEM and examining its predictive validity regarding known associations between exposures and health outcomes (eg, long working hours and strokes).