Related Experiment Video
Updated: Dec 15, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Predicting return to work after long-term sickness absence with subjective health complaints: a prospective cohort
Kristel H N Weerdesteijn1,2,3, Frederieke Schaafsma4,5, Karin Bonefaas-Groenewoud4,5,6
1Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands. k.weerdesteijn@amsterdamumc.nl.
Background:
Long-term sickness absence results in increased risks of permanent disability and a compromised quality of life. Return to work is an important factor in reducing these risks. Little is known about return to work factors for long-term sick-listed workers with subjective health complaints. The aim of this study was to evaluate prognostic factors for partial or full return to a paid job for at least 28 days for long-term sick-listed workers with subjective health complaints, and to compare these factors with those of workers with other disorders.
Methods:
Data from a prospective cohort study of 213 participants with subjective health complaints and 1.037 reference participants were used. The participants answered a questionnaire after 84 weeks of sickness absence. Return to work was measured after one and two years. Univariable logistic regression analyses were performed (P ≤ 0.157) for variables per domain with return to work (i.e. demographic, socio-economic and work-related, health-related, and self-perceived ability). Subsequently, multivariable logistic regression analyses with backward selection (P ≤ 0.157) were performed. Remaining factors were combined in a multivariable and final model (P ≤ 0.05).
Results:
Both for workers with subjective health complaints and for the reference group, non-health-related factors remained statistically significant in the final model. This included receiving a partial or complete work disability benefit (partial: OR 0.62, 95% CI 0.26-1.47 and OR 0.69, 95% CI 0.43-1.12; complete: OR 0.24, 95% CI 0.10-0.58 and OR 0.12, 95% CI 0.07-0.20) and having a positive self-perceived possibility for return to work (OR 1.06, 95% CI 1.01-1.11 and OR 1.08, 95% CI 1.05-1.11).
Conclusions:
Non-health-related factors seem to be more important than health-related factors in predicting return to work after long-term sickness absence. Receiving a work disability benefit and having negative expectations for return to work seem to complicate return to work most for workers with subjective health complaints. With respect to return to work predictors, workers with subjective health complaints do not differ from the reference group.
More Related Videos
06:28Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation
Published on: December 13, 2024
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
Related Concept Videos
Classification of Illness
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
Models of Health Promotion and Illness Prevention II
The agent-host-environment model states that disease results...
Longitudinal Research
Assumptions of Survival Analysis
Observational Studies
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
Factors Affecting Illness
For instance, risk factors are connected to illness,...