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

Abstract

BackgroundPrevious 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.MethodsAgreement 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.ResultsThe 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) %.ConclusionsThe 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.

Parents of children diagnosed with cancer: work situation and sick leave, a five-year post end-of-treatment or a child’s death follow-up study

“…Further, information on sick leave was collected by self-report. However, the sensitivity and specificity of self-reports compared with registry-based sickness absence are acceptable for periods of sick leave not exceeding seven days [22]. In the present study, the majority of parents of survivors (70%) and bereaved parents (57%) reported sick leave of duration less than one week at T7.…”

Occupational exposures and sick leave during pregnancy: results from a Danish cohort study

“…The sensitivity and the specificity were very high for ordinary sick leave, but very low for pregnancyrelated sick leave (26). We believe that this could be due to the exclusion of pregnancy-related sick leave or maternity leave (DREAM code 881) from the analyses.…”

“…recently validated in a study comparing employer registration of sickness absence with DREAM registration (26). The sensitivity and the specificity were very high for ordinary sick leave, but very low for pregnancyrelated sick leave (26).…”

The reliability, validity, and accuracy of self-reported absenteeism from work: A meta-analysis.

“…Two studies were discarded because of incommensurate comparisons, since they matched selfreported and recorded absenteeism referring to different reasons (health problems versus general causes, Short et al, 2009) or to different absence indexes (time lost versus frequency of absence, Beehr & Gupta, 1978). In considering multiple statistics from the same study, we used the following criteria: when a study reported effect sizes or correlations separately for men and women, we averaged them between the two groups (Ferrie et al, 2005;Stapelfeldt, Jensen, Andersen, Fleten, & Nielsen, 2012;Voss, Stark, Alfredsson, Vingård, & Josephson, 2008); when a study reported statistics for multiple absence time periods we retained the 12 month data or that which best approximated that figure, since 12 months was the most common time frame among the studies (Grøvle et al, 2012;Revicki, Irwin, Reblando, & Simon, 2004;Severens, Mulder, Laheij, & Verbeek, 2000); where independent samples were investigated (Kessler et al, 2003), we coded these separately. This screening process resulted in a final set of 30 studies (27 published articles, 2 unpublished master's theses, 1 unpublished conference paper), containing 19 zero-order correlations for the convergent validity meta-analysis of correlations and 21 effect sizes for the accuracy meta-analysis using d. All zero-order correlations and effect sizes were based on independent samples except for the inclusion of Gaziel (2004), which reported both voluntary and involuntary absenteeism.…”