Lindberg Per, Josephson Malin, Alfredsson Lars, Vingård Eva
Department of Clinical Neuroscience, Section for Personal Injury Prevention,Karolinska Institutet, Stockholm, Sweden.
Int Arch Occup Environ Health. 2009 Jan;82(2):227-34. doi: 10.1007/s00420-008-0326-0. Epub 2008 Apr 12.
This study aimed to explore and compare the ability of five instruments for self-rating to predict future sick leave rates.
In three Swedish municipalities 2,252 employees completed a baseline questionnaire and were followed up for 4 years. Five health-oriented instruments for self-rating were used as potential predictors of the two outcome measures no sick leave at all, and one or more spells of long-term sick leave >or=28 days. Positive and negative predictive values as well as Cox proportional hazard ratios (denoted as RRs) adjusted for age and work type were calculated.
The instruments showed no statistical difference in predicting future sick leave for either of the sexes. For no sick leave RRs ranged between 1.27 and 1.52 (women), 1.35 and 1.61 (men); for long-term sick leave RRs ranged between 1.78 and 2.39 (women), 2.87 and 5.53 (men). However, the best prediction of long-term sick leave for men, RR 5.53, 95% confidence interval (CI) 3.37-9.08, was significantly higher than the best prediction for women, RR 2.39, 95% CI 1.97-2.90.
Prediction of long-term sick leave was better than that of no sick leave, and better among men than among women. There was a tendency for somewhat better prediction of future sick leave by multiple-question instruments, but single-question instruments can very well be used in predicting future sick leaves, and crude analyses stratified by sex can be used for screening purposes.
本研究旨在探索并比较五种自评工具预测未来病假率的能力。
在瑞典的三个直辖市,2252名员工完成了一份基线调查问卷,并接受了4年的随访。五种以健康为导向的自评工具被用作两种结果指标的潜在预测因素,即完全无病假,以及一次或多次长期病假(≥28天)。计算了调整年龄和工作类型后的阳性和阴性预测值以及Cox比例风险比(表示为RRs)。
这些工具在预测两性未来病假方面没有统计学差异。对于完全无病假,RRs在女性中为1.27至1.52,在男性中为1.35至1.61;对于长期病假,RRs在女性中为1.78至2.39,在男性中为2.87至5.53。然而,男性长期病假的最佳预测值RR 5.53,95%置信区间(CI)3.37 - 9.08,显著高于女性的最佳预测值RR 2.39,95%CI 1.97 - 2.90。
长期病假的预测优于无病假的预测,男性的预测优于女性。多问题工具在预测未来病假方面有稍好一些的趋势,但单问题工具也完全可用于预测未来病假,按性别进行的粗略分析可用于筛查目的。