INSERM U1085 - Irset, ESTER team, Faculté de santé - Département Médecine, 28 rue Roger Amsler, CS 74521, F-49045 Angers cedex 1, France.
Scand J Work Environ Health. 2024 Dec 1;50(8):653-664. doi: 10.5271/sjweh.4194. Epub 2024 Oct 29.
This study aimed to develop and evaluate a job-exposure matrix (JEM) specific to healthcare workers, JEM Soignances, based on self-reported data.
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.
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.
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).
本研究旨在基于自我报告数据，开发并评估一个特定于医护人员的职业暴露矩阵（JEM），即 Soignances JEM。
该 JEM 是使用 CONSTANCES 队列中的医护人员数据（N=12489）构建的。职业名称和活动领域（例如，医院活动）定义了职业群体。我们评估了涵盖组织、心理社会、物理、化学和生物因素的 24 种暴露。使用 70%的训练样本，应用了多种方法（基于组的频率、CART、随机森林、极端梯度提升机）。使用ROC 曲线下面积（AUC）和 Cohen's Kappa（κ）在剩余的 30%数据上评估性能。提出了两种替代的 JEM，一种仅使用职业名称，另一种则添加医疗机构的规模和类型（公立/私立）来定义职业群体。
所有方法的区分能力（AUC）都相似。我们选择了基于组的频率方法，因为它最容易理解和实施。在纳入的 24 种暴露中，有 15 种具有良好的性能，其中 9 种具有良好的区分能力和适度到中等的一致性，例如工作中的体力劳动（AUC=0.861，κ=0.556）、电离辐射暴露（AUC=0.865，κ=0.457）、搬运重物（AUC=0.840，κ=0.402）、轮班工作（AUC=0.807，κ=0.383）和甲醛暴露（AUC=0.847，κ=0.289）。其余 9 种暴露主要表现出较差到中等的区分能力和较差的一致性。与 Soignances JEM 相比，仅使用职业名称的 JEM 表现不佳，而纳入医疗机构规模和类型的 JEM 则具有相似的结果。
Soignances JEM 具有良好的内部性能和有效性。未来的研究将通过将其与现有 JEM 进行比较，并检查其与暴露和健康结果（例如，长时间工作和中风）之间已知关联的预测有效性，来评估其外部有效性。
