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Finding Risk Factors for Long-Term Sickness Absence Using Classification Trees

In this thesis a model for predicting if someone has an over-risk for long-term sickness absence during the forthcoming year is developed. The model is a classification tree that classifies objects as having high or low risk for long-term sickness absence based on their answers on the Health-Watch form. The HealthWatch form is a questionnaire about health consisting of eleven questions, such as "How do you feel right now?", "How did you sleep last night?", "How is your job satisfaction right now?" etc. As a measure on risk for long-term sickness absence, the Oldenburg Burnout Inventory and a scale for performance based self-esteem are used. Separate models are made for men and for women. The model for women shows good enough performance on a test set for being acceptable as a general model and can be used for prediction. Some conclusions can also be drawn from the additional information given by the classification tree; workload and work atmosphere do not seem to contribute a lot to an in-creased risk for long-term sickness absence, while job satisfaction seems to be one of the most important factors. The model for men performs poorly on a test set, and therefore it is not advisable to use it for prediction or to draw other conclusions from it.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-131751
Date January 2013
CreatorsLundström, Ina
PublisherKTH, Matematisk statistik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationTRITA-MAT-E ; 2013:51

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