Predicting Return to Work in Employees Sick-Listed Due to Minor Mental Disorders
Predicting Return to Work in Employees Sick-Listed Due to Minor Mental Disorders
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DOI：
10.1007/s10926-009-9198-8
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发表时间：
2009-12-01
影响因子：
3.3
通讯作者：
Verhaak, Peter F. M.
中科院分区：
文献类型：
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作者：
Brouwers, Evelien P. M.;Terluin, Berend;Verhaak, Peter F. M.
目的 调查哪些因素可以预测因轻微精神障碍而被列入病假名单的员工 3 个月和 6 个月后重返工作岗位 (RTW)。方法 70 名全科医生招募了 194 名因轻微精神障碍而请病假的受试者。在基线 (T0)、3 个月和 6 个月后（分别为 T1 和 T2），受试者收到一份调查问卷并接受电话采访。使用多元逻辑回归分析，我们开发了三种预测模型来预测 T1 和 T2 时的 RTW。结果 3 个月（T1）后 RTW 率为 38%，6 个月（T2）后 RTW 率为 61%。 T1 时 RTW 的主要负面预测因素是： (a) 病假前问题持续时间超过 3 个月； (b) 躯体化。 T2 时 RTW 的主要负面预测因素是： (a) 病假前问题持续时间超过 3 个月； (b) 在纳入研究之前已休了超过 3 周的病假； (c) 焦虑。对于那些在 T1 时尚未恢复工作的人来说，T2 时 RTW 的主要负面预测因素是： (a) 在纳入研究之前休病假超过 3 周； (b) T1 时的抑郁。模型的预测能力中等，AUC 值在 0.695 至 0.763 之间。结论 RTW 的主要预测因素与问题的严重程度相关。病假发生前出现问题的时间长，以及寻求帮助前病假时间长的，预测3-6个月内RTW的概率相对较小。高基线躯体化和焦虑，以及 3 个月后的高度抑郁使前景变得更糟。由于只需几个问题和症状调查问卷即可轻松评估这些预测因素，因此这为选择高风险员工进行有针对性的干预以防止长期缺勤提供了机会。
Objective To investigate which factors predict return to work (RTW) after 3 and 6 months in employees sick-listed due to minor mental disorders. Methods Seventy GPs recruited 194 subjects at the start of sick leave due to minor mental disorders. At baseline (T0), 3 and 6 months later (T1 and T2, respectively), subjects received a questionnaire and were interviewed by telephone. Using multivariate logistic regression analyses, we developed three prediction models to predict RTW at T1 and T2. Results The RTW rates were 38% after 3 months (T1) and 61% after 6 months (T2). The main negative predictors of RTW at T1 were: (a) a duration of the problems of more than 3 months before sick leave; and (b) somatisation. The main negative predictors of RTW at T2 were: (a) a duration of the problems of more than 3 months before sick leave; (b) more than 3 weeks of sick leave before inclusion in the study; and (c) anxiety. The main negative predictors of RTW at T2 for those who had not resumed work at T1 were: (a) more than 3 weeks of sick leave before inclusion in the study; and (b) depression at T1. The predictive power of the models was moderate with AUC-values between 0.695 and 0.763. Conclusions The main predictors of RTW were associated with the severity of the problems. A long duration of the problems before the occurrence of sick leave and a long duration of sick leave before seeking help predict a relatively small probability to RTW within 3-6 months. High baseline somatisation and anxiety, and high depression after 3 months make the prospect even worse. Since these predictors are readily assessable with just a few questions and a symptom questionnaire, this opens the opportunity to select high-risk employees for a targeted intervention to prevent long-term absenteeism.