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首页> 外文期刊>Scandinavian journal of Work, Environment & Health >Predicting the duration of sickness absence for patients with common mental disorders in occupational health care
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Predicting the duration of sickness absence for patients with common mental disorders in occupational health care

机译:预测职业卫生保健中常见精神障碍患者的疾病缺席时间

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Objectives This study attempted to determine the factors that best predict the duration of absence from work among employees with common mental disorders. Methods A cohort of 188 employees, of whom 102 were teachers, on sick leave with common mental disorders was followed for 1 year. Only information potentially available to the occupational physician during a first consultation was included in the predictive model. The predictive power of the variables was tested using Cox's regression analysis with a stepwise backward selection procedure. The hazard ratios (HR) from the final model were used to deduce a simple prediction rule. The resulting prognostic scores were then used to predict the probability of not returning to work after 3, 6, and 12 months. Calculating the area under the curve from the ROC (receiver operating characteristic) curve tested the discriminative ability of the prediction rule. Results The final Cox's regression model produced the following four predictors of a longer time until return to work: age older than 50 years [HR 0.5, 95% confidence interval (95% CI) 0.3-0.8], expectation of duration absence longer than 3 months (HR 0.5, 95% CI 0.3-0.8), higher educational level (HR 0.5,95% CI 0.3-0.8), and diagnosis depression or anxiety disorder (HR 0.7, 95% CI 0.4-0.9). The resulting prognostic score yielded areas under the curves ranging from 0.68 to 0.73, which represent acceptable discrimination of the rule. Conclusions A prediction rule based on four simple variables can be used by occupational physicians to identify unfavorable cases and to predict the duration of sickness absence.
机译:目的本研究试图确定最能预测患有常见精神障碍的员工缺勤时间的因素。方法对188名雇员(其中102名教师)休病假并患有常见精神疾病的队列进行了为期1年的随访。预测模型仅包括在第一次咨询期间可能对职业医生可用的信息。使用Cox回归分析和逐步向后选择程序测试变量的预测能力。最终模型的危险比(HR)用于推导简单的预测规则。然后将所得的预后评分用于预测3、6和12个月后不返回工作的可能性。根据ROC(接收机工作特性)曲线计算曲线下的面积,检验了预测规则的判别能力。结果最终的Cox回归模型产生了以下四个预测恢复工作时间更长的预测因子:年龄大于50岁[HR 0.5,95%置信区间(95%CI)0.3-0.8],预期持续时间长于3个月(HR 0.5,95%CI 0.3-0.8),较高的教育水平(HR 0.5,95%CI 0.3-0.8)和诊断为抑郁症或焦虑症(HR 0.7,95%CI 0.4-0.9)。所得的预后评分在0.68至0.73的曲线下产生面积,表示该规则的可接受的区分度。结论职业医师可使用基于四个简单变量的预测规则来识别不利病例并预测疾病缺席的持续时间。

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