Centre for Musculoskeletal Research, University of Gävle, Gävle, Sweden.
Appl Ergon. 2010 Mar;41(2):295-304. doi: 10.1016/j.apergo.2009.08.006. Epub 2009 Sep 29.
Ergonomics interventions often focus on reducing exposure in those parts of the job having the highest exposure levels, while leaving other parts unattended. A successful intervention will thus change the form of the job exposure distribution. This disqualifies standard methods for assessing the ability of various exposure measurement strategies to correctly detect an intervention's effect on the overall job exposure of an individual worker, in particular for the safety or ergonomics practitioner who with limited resources can only collect a few measurements. This study used a non-parametric simulation procedure to evaluate the relationship between the number of measurements collected during a self-paced manufacturing job undergoing ergonomics interventions of varying effectiveness, and the probability of correctly determining whether and to which extent the interventions reduced the overall occurrence of pronounced trunk inclination, defined as an inclination of at least 20 degrees . Sixteen video-recordings taken at random times on multiple days for each of three workers were used to estimate the time distribution of each worker's exposure to pronounced trunk inclination. Nine hypothetical ergonomics intervention scenarios were simulated, in which the occurrence of pronounced trunk inclination in the upper 1/8, 1/4, and 1/2 of the job exposure distribution was reduced by 10%, 30% and 50%. Ten exposure measurement strategies were explored, collecting from one to ten pre- and post-intervention exposure samples from an individual worker. For each worker, intervention scenario and sampling strategy, data were bootstrapped from the measured (pre-intervention) and simulated (post-intervention) exposure distributions to generate empirical distributions of the estimated intervention effect. Results showed that for the one to three intervention scenarios that had the greatest effect on the overall occurrence of trunk inclination in the job, one to four pre- and post-intervention measurements, depending on worker, were sufficient to reach an 80% probability of detecting that the intervention did, indeed, have an effect. However, even for the intervention scenario that had the greatest effect on job exposure, seven or more samples were needed for two of the three workers to obtain a probability larger than 50% of estimating the magnitude of the intervention effect to within +/-50% of its true size. For almost all interventions affecting 1/8 or 1/4 of the job, limited exposure sampling led to low probabilities of detecting any intervention effect, let alone its correct size.
工效学干预措施通常侧重于减少工作中暴露水平最高的部位的暴露，而忽略其他部位。因此，成功的干预措施将改变工作暴露分布的形式。这使得评估各种暴露测量策略正确检测个体工人整体工作暴露的干预效果的标准方法失效，特别是对于安全或工效学从业者，他们资源有限，只能收集几次测量。本研究使用非参数模拟程序来评估在经历不同有效性的工效学干预措施的自我 paced 制造工作中收集的测量次数与正确确定干预措施是否以及在多大程度上降低个体工人整体出现明显躯干倾斜的概率之间的关系，定义为至少 20 度的倾斜。为了估计每个工人暴露于明显躯干倾斜的时间分布，从每个工人的多个日子随机时间记录了 16 个视频。模拟了 9 个假设的工效学干预场景，其中上 1/8、1/4 和 1/2 工作暴露分布中的明显躯干倾斜的发生减少了 10%、30%和 50%。探索了 10 种暴露测量策略，从单个工人中收集干预前后的 1 到 10 个暴露样本。对于每个工人、干预场景和采样策略，从测量（干预前）和模拟（干预后）暴露分布中对数据进行了引导，以生成估计的干预效果的经验分布。结果表明，对于对工作中躯干倾斜整体发生影响最大的一到三个干预场景，取决于工人，一到四个干预前后的测量就足以达到 80%的概率来检测干预是否确实有效。然而，即使对于对工作暴露影响最大的干预场景，对于三个工人中的两个，也需要七个或更多样本，才能获得大于 50%的概率来估计干预效果的大小，使其在其真实大小的 +/-50%内。对于影响 1/8 或 1/4 工作的几乎所有干预措施，有限的暴露采样导致检测到任何干预效果的概率很低，更不用说正确估计干预效果的大小了。
