Role clarity, fairness, and organizational climate as predictors of sickness absence: a prospective study in the private sector.
OBJECTIVE
The majority of the research on the effects of the psychosocial work environment on sickness absenteeism has focused on components of job strain and social support among public sector employees without stratification by socioeconomic status. The authors examined less-studied work-related psychosocial predictors of sickness absence in the private sector by socioeconomic status.


METHODS
Questionnaire data on psychosocial factors at work were used to predict the rates of recorded short (1-3 days), long (4-21 days), and very long (over 21 days) sickness absences among 3,850 white- and blue-collar male and female employees in a large-scale enterprise. Multivariate Poisson regression models were adjusted for age, prior absence, and psychosocial factors at work.


RESULTS
In white-collar men, low role clarity was associated with a 3.0 (95% CI 1.3-7.1) times greater rate of very long absences than high role clarity. Low fairness in the division of labor predicted a 1.3-fold (95% CI 1.1-1.5) rate of long absences in blue-collar men. In blue-collar women, poor organizational climate was associated with a 1.6 (95% CI 1.0-2.5) times greater rate of short absence spells than favorable organizational climate but among white-collar women all associations between work-related psychosocial factors and sickness absenteeism were weak.


CONCLUSIONS
These findings indicate that the actions to reduce psychosocial risk factors of sickness absence should match the specific needs of each socioeconomic group.
Väänänen
Ari
A
Finnish Institute of Occupational Health, Department of Psychology, Helsinki, Finland. Ari.Vaananen@ttl.fi
Kalimo
Raija
R
Toppinen-Tanner
Salla
S
Mutanen
Pertti
P
Peiró
José Maria
JM
Kivimäki
Mika
M
Vahtera
Jussi
J
D000328:Adult; D005260:Female; D005387:Finland; D005500:Follow-Up Studies; D006801:Humans; D007588:Job Satisfaction; D008297:Male; D015279:Organizational Culture; D011379:Prognosis; D012044:Regression Analysis; D012380:Role; D018582:Sick Leave / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D017132:Workplace