Reducing absenteeism in hospital cleaning staff: pilot of a theory based intervention.
OBJECTIVE
To develop, pilot, and evaluate a workplace intervention to reduce sickness absence, based on a demand-control-support model of job strain.


METHODS
Changes in the working arrangements of hospital cleaning staff were introduced with the aim of increasing their control over work and the support received at work. The study design was quasi-experimental, with 221 cleaning staff in the intervention group and 91 catering staff in the control group. The dependent variable was the difference in percentage monthly sickness absence between the 12 months preceding and following the intervention. Differences in sickness absence between staff groups for each month after the intervention were compared with differences between staff groups for the equivalent month one year prior to it.


RESULTS
There was a significant reduction in the difference in sickness absence rates between the intervention and control group of 2.3% in the six months after the intervention, compared to the six months before. The difference was not maintained at 12 months.


CONCLUSIONS
These results suggest that a workplace intervention aimed at increasing control and support at work has a small effect on reducing sickness absence among hospital cleaning staff in the short term. Future research should seek to replicate this effect in larger, experimental studies, analyse postulated mediators of such theory based interventions, and develop interventions that maintain improvement.
Michie
S
S
Centre for Outcomes Research and Effectiveness, Department of Psychology, University College London, London, UK. s.michie@ucl.ac.uk
Wren
B
B
Williams
S
S
D000041:Absenteeism; D000328:Adult; D004651:Employment; D006797:Housekeeping, Hospital; D006801:Humans; D007588:Job Satisfaction; D008131:London; D008875:Middle Aged; D016272:Occupational Health; D010559:Personnel Management / Q000379:methods; D010564:Personnel, Hospital; D010865:Pilot Projects; D012189:Retrospective Studies; D012621:Seasons; D018582:Sick Leave / Q000706:statistics & numerical data*