Division Community and Occupational Medicine, Department of Health Sciences, University Medical Center Groningen, Rijksuniversiteit Groningen, Gezondheidswetenschappen, sectie Sociale Geneeskunde, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands.
Center for Leadership and Management Development, Business University Nyenrode, Breukelen, The Netherlands.
Int Arch Occup Environ Health. 2019 May;92(4):501-511. doi: 10.1007/s00420-018-1384-6. Epub 2018 Nov 24.
Frequent absentees are at risk of long-term sickness absence (SA). The aim of the study is to develop prediction models for long-term SA among frequent absentees.
Data were obtained from 53,833 workers who participated in occupational health surveys in the period 2010-2013; 4204 of them were frequent absentees (i.e., employees with ≥ 3 SA spells in the year prior to the survey). The survey data of the frequent absentees were used to develop two prediction models: model 1 including job demands and job resources and model 2 including burnout and work engagement. Discrimination between frequent absentees with and without long-term SA during follow-up was assessed with the area under the receiver operating characteristic curve (AUC); (AUC) ≥ 0.75 was considered useful for practice.
A total of 3563 employees had complete data for analyses and 685 (19%) of them had long-term SA during 1-year follow-up. The final model 1 included age, gender, education, marital status, prior long-term SA, work pace, role clarity and learning opportunities. Discrimination between frequent absentees with and without long-term SA was significant (AUC 0.623; 95% CI 0.601-0.646), but not useful for practice. Model 2 showed comparable discrimination (AUC 0.624; 95% CI 0.596-0.651) with age, gender, education, marital status, prior long-term SA, burnout and work engagement as predictor variables. Differentiating by gender or sickness absence cause did not result in better discrimination.
Both prediction models discriminated significantly between frequent absentees with and without long-term SA during 1-year follow-up, but have to be further developed for use in healthcare practice.
频繁缺勤者有长期病假(SA)的风险。本研究旨在为频繁缺勤者的长期 SA 制定预测模型。
数据来自 2010-2013 年期间参加职业健康调查的 53833 名工人;其中 4204 人是频繁缺勤者(即在调查前一年有≥3 次 SA 发作的员工)。使用频繁缺勤者的调查数据开发了两个预测模型:模型 1 包括工作需求和工作资源,模型 2 包括倦怠和工作投入。使用受试者工作特征曲线下面积(AUC)评估随访期间频繁缺勤者与无长期 SA 者之间的区分度;(AUC)≥0.75 被认为对实践有用。
共有 3563 名员工有完整的数据进行分析,其中 685 名(19%)在 1 年随访期间患有长期 SA。最终的模型 1 包括年龄、性别、教育程度、婚姻状况、既往长期 SA、工作节奏、角色清晰度和学习机会。频繁缺勤者与无长期 SA 者之间的区分度显著(AUC 0.623;95%CI 0.601-0.646),但对实践没有帮助。模型 2 显示了类似的区分度(AUC 0.624;95%CI 0.596-0.651),预测变量为年龄、性别、教育程度、婚姻状况、既往长期 SA、倦怠和工作投入。按性别或病假原因进行区分并未导致更好的区分度。
这两个预测模型在 1 年随访期间显著区分了频繁缺勤者与无长期 SA 者,但需要进一步开发,以便在医疗保健实践中使用。