Email updates

Keep up to date with the latest news and content from BMC Public Health and BioMed Central.

Open Access Research article

Validation of sick leave measures: self-reported sick leave and sickness benefit data from a Danish national register compared to multiple workplace-registered sick leave spells in a Danish municipality

Christina Malmose Stapelfeldt12*, Chris Jensen2, Niels Trolle Andersen3, Nils Fleten24 and Claus Vinther Nielsen12

Author affiliations

1 Section of Social Medicine and Rehabilitation, Deparment of Public Health, Aarhus University, Aarhus, Denmark

2 Public Health and Quality Improvement, Aarhus, Central Denmark Region, Denmark

3 Section of Biostatistics, Department of Public Health, Aarhus University, Aarhus, Denmark

4 Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway

For all author emails, please log on.

Citation and License

BMC Public Health 2012, 12:661  doi:10.1186/1471-2458-12-661

Published: 15 August 2012

Abstract

Background

Previous validation studies of sick leave measures have focused on self-reports. Register-based sick leave data are considered to be valid; however methodological problems may be associated with such data. A Danish national register on sickness benefit (DREAM) has been widely used in sick leave research. On the basis of sick leave records from 3,554 and 2,311 eldercare workers in 14 different workplaces, the aim of this study was to: 1) validate registered sickness benefit data from DREAM against workplace-registered sick leave spells of at least 15 days; 2) validate self-reported sick leave days during one year against workplace-registered sick leave.

Methods

Agreement between workplace-registered sick leave and DREAM-registered sickness benefit was reported as sensitivities, specificities and positive predictive values. A receiver-operating characteristic curve and a Bland-Altman plot were used to study the concordance with sick leave duration of the first spell. By means of an analysis of agreement between self-reported and workplace-registered sick leave sensitivity and specificity was calculated. Ninety-five percent confidence intervals (95% CI) were used.

Results

The probability that registered DREAM data on sickness benefit agrees with workplace-registered sick leave of at least 15 days was 96.7% (95% CI: 95.6-97.6). Specificity was close to 100% (95% CI: 98.3-100). The registered DREAM data on sickness benefit overestimated the duration of sick leave spells by an average of 1.4 (SD: 3.9) weeks. Separate analysis on pregnancy-related sick leave revealed a maximum sensitivity of 20% (95% CI: 4.3-48.1).

The sensitivity of self-reporting at least one or at least 56 sick leave day/s was 94.5 (95% CI: 93.4 – 95.5) % and 58.5 (95% CI: 51.1 – 65.6) % respectively. The corresponding specificities were 85.3 (95% CI: 81.4 – 88.6) % and 98.9 (95% CI: 98.3 – 99.3) %.

Conclusions

The DREAM register offered valid measures of sick leave spells of at least 15 days among eldercare employees. Pregnancy-related sick leave should be excluded in studies planning to use DREAM data on sickness benefit. Self-reported sick leave became more imprecise when number of absence days increased, but the sensitivity and specificity were acceptable for lengths not exceeding one week.

Keywords:
Agreement; Eldercare sector; Public transfer payment; Register data; Self-report; Sensitivity; Sick leave; Specificity; Validation; Workplace record