Background: Sickness absence is very high in Sweden. The reasons for this phenomenon are not well known. The aim of this study was to investigate the association between degree of self-reported sickness absence and health. The hypothesis was that individuals with long-term sickness absence would report more symptoms and lower self-rated health. Another hypothesis was that women are more likely to selfrate psychiatric diagnoses compared to men, who are more likely to self-rate musculoskeletal diagnoses.

BackgroundLong-term sickness absence is one of the main risk factors for permanent exit out of the labour market. Early identification of the condition is essential to facilitate return to work. The aim of this study was to analyse possible determinants of return to work and their relative impact.MethodsAll 943 subjects aged 18 to 63 years, sickness certified at a Primary Health Care Centre in Sweden from 1 January until 31 August 2004, were followed up for three years. Baseline information on sex, age, sick leave diagnosis, employment status, extent of sick leave, and sickness absence during the year before baseline was obtained, as was information on all compensated days of sick leave, disability pension and death during follow-up.ResultsSlightly more than half the subjects were women, mean age was 39 years. Half of the study population returned to work within 14 days after baseline, and after three years only 15 subjects were still on sick leave. In multivariate proportional hazards regression analysis the extent of previous sick leave, age, being on part-time sick leave, and having a psychiatric, musculoskeletal, cardiovascular, nervous disease, digestive system, or injury or poisoning diagnosis decreased the return to work rate, while being employed increased it. Marital status, sex, being born in Sweden, citizenship, and annual salary had no influence. In logistic regression analyses across follow-up time these variables altogether explained 88-90% of return to work variation.ConclusionsReturn to work was positively or negatively associated by a number of variables easily accessible in the GP’s office. Track record data in the form of previous sick leave was the most influential variable.

There is a need to educate and train registered nurses in social insurance medicine to provide high-quality nursing for patients on or at risk for sick leave.

Aim The purpose was to analyse the properties of two models for the assessment of return to work after sickness certification, a manual one based on clinical judgement including non-measurable information (‘gut feeling’), and a computer-based one.Study population All subjects aged 18 to 63 years, sickness-certified at a primary health care centre in Sweden during 8 months (n = 943), and followed up for 3 years.Methods Baseline information included age, sex, occupational status, sickness certification diagnosis, full-time or part-time current sick-leave, and sick-leave days during the past year. Follow-up information included first and last day of each occurring sick spell. In the manual model all subjects were classified, based on baseline information and gut feeling, into a high-risk (n = 447) or a low-risk group (n = 496) regarding not returning to work when the present certificate expired. It was evaluated with a Cox’s analysis, including time and return to work as dependent variables and risk group assignment as the independent variable, while in the computer-based model the baseline variables were entered as independent variables.Results Concordance between actual return to work and return to work predicted by the analysis model was 73%–76% during the first 28–180 days in the manual model, and approximately 10% units higher in the computer-based model. Based on the latter, three nomograms were constructed providing detailed information on the probability of return to work.Conclusion The computer-based model had a higher precision and gave more detailed information than the manual model.