TY - JOUR
T1 - Determinants of sick-leave duration
T2 - A tool for managers?
AU - Flach, P.A.
AU - Krol, B.
AU - Groothoff, J.W.
PY - 2008/9
Y1 - 2008/9
N2 - AIMS: To provide managers with tools to manage episodes of sick-leave of their employees, the influence of factors such as age, gender, duration of tenure, working full-time or part-time, cause and history of sick-leave, salary and education on sick-leave duration was studied. METHOD: In a cross-sectional study, data derived from the 2005 sick-leave files of a Dutch university were examined. Odds ratios of the single risk factors were calculated for short spells (or=91 days) of sick-leave. Next, these factors were studied in multiple regression models. RESULTS: Age, gender, duration of employment, cause and history of sick-leave, salary and membership of scientific staff, studied as single factors, have a significant influence on sick-leave duration. In multiple models, this influence remains for gender, salary, age, and history and cause of sick-leave. Only in medium or long spells and regarding the risk for a long or an extended spell do the predictive values of models consisting of psychological factors, work-related factors, salary and gender become reasonable. CONCLUSIONS: The predictive value of the risk factors used in this study is limited, and varies with the duration of the sick-leave spell. Only the risk for an extended spell of sick-leave as compared to a medium or long spell is reasonably predicted. Factors contributing to this risk may be used as tools in decision-making
AB - AIMS: To provide managers with tools to manage episodes of sick-leave of their employees, the influence of factors such as age, gender, duration of tenure, working full-time or part-time, cause and history of sick-leave, salary and education on sick-leave duration was studied. METHOD: In a cross-sectional study, data derived from the 2005 sick-leave files of a Dutch university were examined. Odds ratios of the single risk factors were calculated for short spells (or=91 days) of sick-leave. Next, these factors were studied in multiple regression models. RESULTS: Age, gender, duration of employment, cause and history of sick-leave, salary and membership of scientific staff, studied as single factors, have a significant influence on sick-leave duration. In multiple models, this influence remains for gender, salary, age, and history and cause of sick-leave. Only in medium or long spells and regarding the risk for a long or an extended spell do the predictive values of models consisting of psychological factors, work-related factors, salary and gender become reasonable. CONCLUSIONS: The predictive value of the risk factors used in this study is limited, and varies with the duration of the sick-leave spell. Only the risk for an extended spell of sick-leave as compared to a medium or long spell is reasonably predicted. Factors contributing to this risk may be used as tools in decision-making
KW - determinants
KW - duration
KW - predictor
KW - sickness absence
KW - MENTAL-HEALTH PROBLEMS
KW - DISABILITY PENSION
KW - MAASTRICHT COHORT
KW - ABSENCE
KW - WORK
KW - PREDICTORS
KW - INJURY
KW - GENDER
KW - RETURN
KW - EMPLOYEES
U2 - 10.1177/1403494808092251
DO - 10.1177/1403494808092251
M3 - Article
SN - 1403-4948
VL - 36
SP - 713
EP - 719
JO - Scandinavian Journal of Public Health
JF - Scandinavian Journal of Public Health
IS - 7
ER -